Clinical Trials

Imaging the Nucleus Accumbens in Major Depressed Patients 'Treated With PramipexoleNot Recruiting

We hope to learn how a brain circuit that is important to the understanding of depression,
anhedonia and positive affect responds to a novel pharmaceutical treatment for depression and
related symptoms. Adults who have a diagnosis of major depression and are not completely
responsive to antidepressant medication will be sought out for participation; as will an
equal number of adults not suffering from the disorder. Those suffering from depression will
be given pramipexole, an investigational medication for eight weeks during which information
will be collected about mood, cognition, and brain function. Adults not suffering from
depression will also be evaluated with these measures.

Stanford is currently not accepting patients for this trial.For more information, please contact Jennifer Keller, PHD, 650-724-0070.

Abstract

Mathematical disabilities (MD) have a negative life-long impact on professional success, employment, and health outcomes. Yet little is known about the intrinsic functional brain organization that contributes to poor math skills in affected children. It is now increasingly recognized that math cognition requires coordinated interaction within a large-scale fronto-parietal network anchored in the intraparietal sulcus (IPS). Here we characterize intrinsic functional connectivity within this IPS-network in children with MD, relative to a group of typically developing (TD) children who were matched on age, gender, IQ, working memory, and reading abilities. Compared to TD children, children with MD showed hyper-connectivity of the IPS with a bilateral fronto-parietal network. Importantly, aberrant IPS connectivity patterns accurately discriminated children with MD and TD children, highlighting the possibility for using IPS connectivity as a brain-based biomarker of MD. To further investigate regional abnormalities contributing to network-level deficits in children with MD, we performed whole-brain analyses of intrinsic low-frequency fluctuations. Notably, children with MD showed higher low-frequency fluctuations in multiple fronto-parietal areas that overlapped with brain regions that exhibited hyper-connectivity with the IPS. Taken together, our findings suggest that MD in children is characterized by robust network-level aberrations, and is not an isolated dysfunction of the IPS. We hypothesize that intrinsic hyper-connectivity and enhanced low-frequency fluctuations may limit flexible resource allocation, and contribute to aberrant recruitment of task-related brain regions during numerical problem solving in children with MD.

Abstract

One of the most fundamental features of the human brain is its ability to detect and attend to salient goal-relevant events in a flexible manner. The salience network (SN), anchored in the anterior insula and the dorsal anterior cingulate cortex, plays a crucial role in this process through rapid detection of goal-relevant events and facilitation of access to appropriate cognitive resources. Here, we leverage the subsecond resolution of large multisession fMRI datasets from the Human Connectome Project and apply novel graph-theoretical techniques to investigate the dynamic spatiotemporal organization of the SN. We show that the large-scale brain dynamics of the SN are characterized by several distinctive and robust properties. First, the SN demonstrated the highest levels of flexibility in time-varying connectivity with other brain networks, including the frontoparietal network (FPN), the cingulate-opercular network (CON), and the ventral and dorsal attention networks (VAN and DAN). Second, dynamic functional interactions of the SN were among the most spatially varied in the brain. Third, SN nodes maintained a consistently high level of network centrality over time, indicating that this network is a hub for facilitating flexible cross-network interactions. Fourth, time-varying connectivity profiles of the SN were distinct from all other prefrontal control systems. Fifth, temporal flexibility of the SN uniquely predicted individual differences in cognitive flexibility. Importantly, each of these results was also observed in a second retest dataset, demonstrating the robustness of our findings. Our study provides fundamental new insights into the distinct dynamic functional architecture of the SN and demonstrates how this network is uniquely positioned to facilitate interactions with multiple functional systems and thereby support a wide range of cognitive processes in the human brain.

Abstract

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Abstract

Anhedonia, the reduced ability to experience pleasure in response to otherwise rewarding stimuli, is a core symptom of major depressive disorder (MDD). Although the posterior ventromedial prefrontal cortex (pVMPFC) and its functional connections have been consistently implicated in MDD, their roles in anhedonia remain poorly understood. Furthermore, it is unknown whether anhedonia is primarily associated with intrinsic 'resting-state' pVMPFC functional connectivity or an inability to modulate connectivity in a context-specific manner. To address these gaps, a pVMPFC region of interest was first identified using activation likelihood estimation meta-analysis. pVMPFC connectivity was then examined in relation to anhedonia and general distress symptoms of depression, using both resting-state and task-based functional magnetic resonance imaging involving pleasant music, in current MDD and healthy control groups. In MDD, pVMPFC connectivity was negatively correlated with anhedonia but not general distress during music listening in key reward- and emotion-processing regions, including nucleus accumbens, ventral tegmental area/substantia nigra, orbitofrontal cortex and insula, as well as fronto-temporal regions involved in tracking complex sound sequences, including middle temporal gyrus and inferior frontal gyrus. No such dissociations were observed in the healthy controls, and resting-state pVMPFC connectivity did not dissociate anhedonia from general distress in either group. Our findings demonstrate that anhedonia in MDD is associated with context-specific deficits in pVMPFC connectivity with the mesolimbic reward system when encountering pleasurable stimuli, rather than a static deficit in intrinsic resting-state connectivity. Critically, identification of functional circuits associated with anhedonia better characterizes MDD heterogeneity and may help track of one of its core symptoms.

Abstract

Math anxiety is a negative emotional reaction that is characterized by feelings of stress and anxiety in situations involving mathematical problem solving. High math-anxious individuals tend to avoid situations involving mathematics and are less likely to pursue science, technology, engineering, and math-related careers than those with low math anxiety. Math anxiety during childhood, in particular, has adverse long-term consequences for academic and professional success. Identifying cognitive interventions and brain mechanisms by which math anxiety can be ameliorated in children is therefore critical. Here we investigate whether an intensive 8 week one-to-one cognitive tutoring program designed to improve mathematical skills reduces childhood math anxiety, and we identify the neurobiological mechanisms by which math anxiety can be reduced in affected children. Forty-six children in grade 3, a critical early-onset period for math anxiety, participated in the cognitive tutoring program. High math-anxious children showed a significant reduction in math anxiety after tutoring. Remarkably, tutoring remediated aberrant functional responses and connectivity in emotion-related circuits anchored in the basolateral amygdala. Crucially, children with greater tutoring-induced decreases in amygdala reactivity had larger reductions in math anxiety. Our study demonstrates that sustained exposure to mathematical stimuli can reduce math anxiety and highlights the key role of the amygdala in this process. Our findings are consistent with models of exposure-based therapy for anxiety disorders and have the potential to inform the early treatment of a disability that, if left untreated in childhood, can lead to significant lifelong educational and socioeconomic consequences in affected individuals.Math anxiety during early childhood has adverse long-term consequences for academic and professional success. It is therefore important to identify ways to alleviate math anxiety in young children. Surprisingly, there have been no studies of cognitive interventions and the underlying neurobiological mechanisms by which math anxiety can be ameliorated in young children. Here, we demonstrate that intensive 8 week one-to-one cognitive tutoring not only reduces math anxiety but also remarkably remediates aberrant functional responses and connectivity in emotion-related circuits anchored in the amygdala. Our findings are likely to propel new ways of thinking about early treatment of a disability that has significant implications for improving each individual's academic and professional chances of success in today's technological society that increasingly demands strong quantitative skills.

Abstract

Early numerical proficiency lays the foundation for acquiring quantitative skills essential in today's technological society. Identification of cognitive and brain markers associated with long-term growth of children's basic numerical computation abilities is therefore of utmost importance. Previous attempts to relate brain structure and function to numerical competency have focused on behavioral measures from a single time point. Thus, little is known about the brain predictors of individual differences in growth trajectories of numerical abilities. Using a longitudinal design, with multimodal imaging and machine-learning algorithms, we investigated whether brain structure and intrinsic connectivity in early childhood are predictive of 6 year outcomes in numerical abilities spanning childhood and adolescence. Gray matter volume at age 8 in distributed brain regions, including the ventrotemporal occipital cortex (VTOC), the posterior parietal cortex, and the prefrontal cortex, predicted longitudinal gains in numerical, but not reading, abilities. Remarkably, intrinsic connectivity analysis revealed that the strength of functional coupling among these regions also predicted gains in numerical abilities, providing novel evidence for a network of brain regions that works in concert to promote numerical skill acquisition. VTOC connectivity with posterior parietal, anterior temporal, and dorsolateral prefrontal cortices emerged as the most extensive network predicting individual gains in numerical abilities. Crucially, behavioral measures of mathematics, IQ, working memory, and reading did not predict children's gains in numerical abilities. Our study identifies, for the first time, functional circuits in the human brain that scaffold the development of numerical skills, and highlights potential biomarkers for identifying children at risk for learning difficulties.Children show substantial individual differences in math abilities and ease of math learning. Early numerical abilities provide the foundation for future academic and professional success in an increasingly technological society. Understanding the early identification of poor math skills has therefore taken on great significance. This work provides important new insights into brain structure and connectivity measures that can predict longitudinal growth of children's math skills over a 6 year period, and may eventually aid in the early identification of children who might benefit from targeted interventions.

Abstract

Competency with numbers is essential in today's society; yet, up to 20% of children exhibit moderate to severe mathematical learning disabilities (MLD). Behavioural intervention can be effective, but the neurobiological mechanisms underlying successful intervention are unknown. Here we demonstrate that eight weeks of 1:1 cognitive tutoring not only remediates poor performance in children with MLD, but also induces widespread changes in brain activity. Neuroplasticity manifests as normalization of aberrant functional responses in a distributed network of parietal, prefrontal and ventral temporal-occipital areas that support successful numerical problem solving, and is correlated with performance gains. Remarkably, machine learning algorithms show that brain activity patterns in children with MLD are significantly discriminable from neurotypical peers before, but not after, tutoring, suggesting that behavioural gains are not due to compensatory mechanisms. Our study identifies functional brain mechanisms underlying effective intervention in children with MLD and provides novel metrics for assessing response to intervention.

Abstract

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development-the transition from procedure-based to memory-based problem-solving strategies-are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7-9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

Underconnectivity between voice-selective cortex and reward circuitry in children with autismPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAAbrams, D. A., Lynch, C. J., Cheng, K. M., Phillips, J., Supekar, K., Ryali, S., Uddin, L. Q., Menon, V.2013; 110 (29): 12060-12065

Abstract

Individuals with autism spectrum disorders (ASDs) often show insensitivity to the human voice, a deficit that is thought to play a key role in communication deficits in this population. The social motivation theory of ASD predicts that impaired function of reward and emotional systems impedes children with ASD from actively engaging with speech. Here we explore this theory by investigating distributed brain systems underlying human voice perception in children with ASD. Using resting-state functional MRI data acquired from 20 children with ASD and 19 age- and intelligence quotient-matched typically developing children, we examined intrinsic functional connectivity of voice-selective bilateral posterior superior temporal sulcus (pSTS). Children with ASD showed a striking pattern of underconnectivity between left-hemisphere pSTS and distributed nodes of the dopaminergic reward pathway, including bilateral ventral tegmental areas and nucleus accumbens, left-hemisphere insula, orbitofrontal cortex, and ventromedial prefrontal cortex. Children with ASD also showed underconnectivity between right-hemisphere pSTS, a region known for processing speech prosody, and the orbitofrontal cortex and amygdala, brain regions critical for emotion-related associative learning. The degree of underconnectivity between voice-selective cortex and reward pathways predicted symptom severity for communication deficits in children with ASD. Our results suggest that weak connectivity of voice-selective cortex and brain structures involved in reward and emotion may impair the ability of children with ASD to experience speech as a pleasurable stimulus, thereby impacting language and social skill development in this population. Our study provides support for the social motivation theory of ASD.

Neural predictors of individual differences in response to math tutoring in primary-grade school children.Proceedings of the National Academy of Sciences of the United States of AmericaSupekar, K., Swigart, A. G., Tenison, C., Jolles, D. D., Rosenberg-Lee, M., Fuchs, L., Menon, V.2013; 110 (20): 8230-8235

Abstract

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8-9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.

Immature integration and segregation of emotion-related brain circuitry in young childrenPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAQin, S., Young, C. B., Supekar, K., Uddin, L. Q., Menon, V.2012; 109 (20): 7941-7946

Abstract

The human brain undergoes protracted development, with dramatic changes in expression and regulation of emotion from childhood to adulthood. The amygdala is a brain structure that plays a pivotal role in emotion-related functions. Investigating developmental characteristics of the amygdala and associated functional circuits in children is important for understanding how emotion processing matures in the developing brain. The basolateral amygdala (BLA) and centromedial amygdala (CMA) are two major amygdalar nuclei that contribute to distinct functions via their unique pattern of interactions with cortical and subcortical regions. Almost nothing is currently known about the maturation of functional circuits associated with these amygdala nuclei in the developing brain. Using intrinsic connectivity analysis of functional magnetic resonance imaging data, we investigated developmental changes in functional connectivity of the BLA and CMA in twenty-four 7- to 9-y-old typically developing children compared with twenty-four 19- to 22-y-old healthy adults. Children showed significantly weaker intrinsic functional connectivity of the amygdala with subcortical, paralimbic, and limbic structures, polymodal association, and ventromedial prefrontal cortex. Importantly, target networks associated with the BLA and CMA exhibited greater overlap and weaker dissociation in children. In line with this finding, children showed greater intraamygdala connectivity between the BLA and CMA. Critically, these developmental differences were reproducibly identified in a second independent cohort of adults and children. Taken together, our findings point toward weak integration and segregation of amygdala circuits in young children. These immature patterns of amygdala connectivity have important implications for understanding typical and atypical development of emotion-related brain circuitry.

Musical rhythm spectra from Bach to Joplin obey a 1/f power lawPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICALevitin, D. J., Chordia, P., Menon, V.2012; 109 (10): 3716-3720

Abstract

Much of our enjoyment of music comes from its balance of predictability and surprise. Musical pitch fluctuations follow a 1/f power law that precisely achieves this balance. Musical rhythms, especially those of Western classical music, are considered highly regular and predictable, and this predictability has been hypothesized to underlie rhythm's contribution to our enjoyment of music. Are musical rhythms indeed entirely predictable and how do they vary with genre and composer? To answer this question, we analyzed the rhythm spectra of 1,788 movements from 558 compositions of Western classical music. We found that an overwhelming majority of rhythms obeyed a 1/f(β) power law across 16 subgenres and 40 composers, with β ranging from ∼0.5-1. Notably, classical composers, whose compositions are known to exhibit nearly identical 1/f pitch spectra, demonstrated distinctive 1/f rhythm spectra: Beethoven's rhythms were among the most predictable, and Mozart's among the least. Our finding of the ubiquity of 1/f rhythm spectra in compositions spanning nearly four centuries demonstrates that, as with musical pitch, musical rhythms also exhibit a balance of predictability and surprise that could contribute in a fundamental way to our aesthetic experience of music. Although music compositions are intended to be performed, the fact that the notated rhythms follow a 1/f spectrum indicates that such structure is no mere artifact of performance or perception, but rather, exists within the written composition before the music is performed. Furthermore, composers systematically manipulate (consciously or otherwise) the predictability in 1/f rhythms to give their compositions unique identities.

Abstract

Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI) to investigate the maturation of control processes underlying problem solving skills in 7-9 year-old children. Our analysis focused on two key neurocognitive networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience network, anchored in anterior insula (AI), ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal central executive network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We found that, by age 9, the AI node of the salience network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the central executive network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. The quantitative approach developed is likely to be useful in investigating neurodevelopmental disorders, in which control processes are impaired, such as autism and ADHD.

Abstract

Brain structural and functional development, throughout childhood and into adulthood, underlies the maturation of increasingly sophisticated cognitive abilities. High-level attentional and cognitive control processes rely on the integrity of, and dynamic interactions between, core neurocognitive networks. The right fronto-insular cortex (rFIC) is a critical component of a salience network (SN) that mediates interactions between large-scale brain networks involved in externally oriented attention [central executive network (CEN)] and internally oriented cognition [default mode network (DMN)]. How these systems reconfigure and mature with development is a critical question for cognitive neuroscience, with implications for neurodevelopmental pathologies affecting brain connectivity. Using functional and effective connectivity measures applied to fMRI data, we examine interactions within and between the SN, CEN, and DMN. We find that functional coupling between key network nodes is stronger in adults than in children, as are causal links emanating from the rFIC. Specifically, the causal influence of the rFIC on nodes of the SN and CEN was significantly greater in adults compared with children. Notably, these results were entirely replicated on an independent dataset of matched children and adults. Developmental changes in functional and effective connectivity were related to structural connectivity along these links. Diffusion tensor imaging tractography revealed increased structural integrity in adults compared with children along both within- and between-network pathways associated with the rFIC. These results suggest that structural and functional maturation of rFIC pathways is a critical component of the process by which human brain networks mature during development to support complex, flexible cognitive processes in adulthood.

Abstract

The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology. I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism. Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders.

Abstract

An understanding of how the human brain produces cognition ultimately depends on knowledge of large-scale brain organization. Although it has long been assumed that cognitive functions are attributable to the isolated operations of single brain areas, we demonstrate that the weight of evidence has now shifted in support of the view that cognition results from the dynamic interactions of distributed brain areas operating in large-scale networks. We review current research on structural and functional brain organization, and argue that the emerging science of large-scale brain networks provides a coherent framework for understanding of cognition. Critically, this framework allows a principled exploration of how cognitive functions emerge from, and are constrained by, core structural and functional networks of the brain.

Abstract

Little is known about the neural abnormalities underlying generalized anxiety disorder (GAD). Studies in other anxiety disorders have implicated the amygdala, but work in GAD has yielded conflicting results. The amygdala is composed of distinct subregions that interact with dissociable brain networks, which have been studied only in experimental animals. A functional connectivity approach at the subregional level may therefore yield novel insights into GAD.To determine whether distinct connectivity patterns can be reliably identified for the basolateral (BLA) and centromedial (CMA) subregions of the human amygdala, and to examine subregional connectivity patterns and potential compensatory amygdalar connectivity in GAD.Cross-sectional study.Academic medical center.Two cohorts of healthy control subjects (consisting of 17 and 31 subjects) and 16 patients with GAD.Functional connectivity with cytoarchitectonically determined BLA and CMA regions of interest, measured during functional magnetic resonance imaging performed while subjects were resting quietly in the scanner. Amygdalar gray matter volume was also investigated with voxel-based morphometry.Reproducible subregional differences in large-scale connectivity were identified in both cohorts of healthy controls. The BLA was differentially connected with primary and higher-order sensory and medial prefrontal cortices. The CMA was connected with the midbrain, thalamus, and cerebellum. In GAD patients, BLA and CMA connectivity patterns were significantly less distinct, and increased gray matter volume was noted primarily in the CMA. Across the subregions, GAD patients had increased connectivity with a previously characterized frontoparietal executive control network and decreased connectivity with an insula- and cingulate-based salience network.Our findings provide new insights into the functional neuroanatomy of the human amygdala and converge with connectivity studies in experimental animals. In GAD, we find evidence of an intra-amygdalar abnormality and engagement of a compensatory frontoparietal executive control network, consistent with cognitive theories of GAD.

Abstract

Autism is a complex neurodevelopmental disorder of unknown etiology. While the past decade has witnessed a proliferation of neuroimaging studies of autism, theoretical approaches for understanding systems-level brain abnormalities remain poorly developed. We propose a novel anterior insula-based systems-level model for investigating the neural basis of autism, synthesizing recent advances in brain network functional connectivity with converging evidence from neuroimaging studies in autism. The anterior insula is involved in interoceptive, affective and empathic processes, and emerging evidence suggests it is part of a "salience network" integrating external sensory stimuli with internal states. Network analysis indicates that the anterior insula is uniquely positioned as a hub mediating interactions between large-scale networks involved in externally and internally oriented cognitive processing. A recent meta-analysis identifies the anterior insula as a consistent locus of hypoactivity in autism. We suggest that dysfunctional anterior insula connectivity plays an important role in autism. Critical examination of these abnormalities from a systems neuroscience perspective should be a priority for further research on the neurobiology of autism.

Abstract

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Abstract

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity.

Abstract

Little is currently known about dynamic brain networks involved in high-level cognition and their ontological basis. Here we develop a novel Variational Bayesian Hidden Markov Model (VB-HMM) to investigate dynamic temporal properties of interactions between salience (SN), default mode (DMN), and central executive (CEN) networks-three brain systems that play a critical role in human cognition. In contrast to conventional models, VB-HMM revealed multiple short-lived states characterized by rapid switching and transient connectivity between SN, CEN, and DMN. Furthermore, the three "static" networks occurred in a segregated state only intermittently. Findings were replicated in two adult cohorts from the Human Connectome Project. VB-HMM further revealed immature dynamic interactions between SN, CEN, and DMN in children, characterized by higher mean lifetimes in individual states, reduced switching probability between states and less differentiated connectivity across states. Our computational techniques provide new insights into human brain network dynamics and its maturation with development.

Abstract

Cognitive development is shaped by brain plasticity during childhood, yet little is known about changes in large-scale functional circuits associated with learning in academically relevant cognitive domains such as mathematics. Here, we investigate plasticity of intrinsic brain circuits associated with one-on-one math tutoring and its relation to individual differences in children's learning. We focused on functional circuits associated with the intraparietal sulcus (IPS) and angular gyrus (AG), cytoarchitectonically distinct subdivisions of the human parietal cortex with different roles in numerical cognition. Tutoring improved performance and strengthened IPS connectivity with the lateral prefrontal cortex, ventral temporal-occipital cortex, and hippocampus. Crucially, increased IPS connectivity was associated with individual performance gains, highlighting the behavioral significance of plasticity in IPS circuits. Tutoring-related changes in IPS connectivity were distinct from those of the adjacent AG, which did not predict performance gains. Our findings provide new insights into plasticity of functional brain circuits associated with the development of specialized cognitive skills in children.

Abstract

Causal estimation methods are increasingly being used to investigate functional brain networks in fMRI, but there are continuing concerns about the validity of these methods.Multivariate Dynamical Systems (MDS) is a state-space method for estimating dynamic causal interactions in fMRI data. Here we validate MDS using benchmark simulations as well as simulations from a more realistic stochastic neurophysiological model. Finally, we applied MDS to investigate dynamic casual interactions in a fronto-cingulate-parietal control network using Human Connectome Project (HCP) data acquired during performance of a working memory task. Crucially, since the ground truth in experimental data is unknown, we conducted novel stability analysis to determine robust causal interactions within this network.MDS accurately recovered dynamic causal interactions with an area under receiver operating characteristic (AUC) above 0.7 for benchmark datasets and AUC above 0.9 for datasets generated using the neurophysiological model. In experimental fMRI data, bootstrap procedures revealed a stable pattern of causal influences from the anterior insula to other nodes of the fronto-cingulate-parietal network.MDS is effective in estimating dynamic causal interactions in both the benchmark and neurophysiological model based datasets in terms of AUC, sensitivity and false positive rates.Our findings demonstrate that MDS can accurately estimate causal interactions in fMRI data. Neurophysiological models and stability analysis provide a general framework for validating computational methods designed to estimate causal interactions in fMRI. The right anterior insula functions as a causal hub during working memory.

Abstract

The ability to anticipate and detect behaviorally salient stimuli is important for virtually all adaptive behaviors, including inhibitory control that requires the withholding of prepotent responses when instructed by external cues. Although right fronto-operculum-insula (FOI), encompassing the anterior insular cortex (rAI) and inferior frontal cortex (rIFC), involvement in inhibitory control is well established, little is known about signaling mechanisms underlying their differential roles in detection and anticipation of salient inhibitory cues. Here we use 2 independent functional magnetic resonance imaging data sets to investigate dynamic causal interactions of the rAI and rIFC, with sensory cortex during detection and anticipation of inhibitory cues. Across 2 different experiments involving auditory and visual inhibitory cues, we demonstrate that primary sensory cortex has a stronger causal influence on rAI than on rIFC, suggesting a greater role for the rAI in detection of salient inhibitory cues. Crucially, a Bayesian prediction model of subjective trial-by-trial changes in inhibitory cue anticipation revealed that the strength of causal influences from rIFC to rAI increased significantly on trials in which participants had higher anticipation of inhibitory cues. Together, these results demonstrate the dissociable bottom-up and top-down roles of distinct FOI regions in detection and anticipation of behaviorally salient cues across multiple sensory modalities.

Abstract

The medial temporal lobe (MTL), encompassing the hippocampus and parahippocampal gyrus (PHG), is a heterogeneous structure which plays a critical role in memory and cognition. Here, we investigate functional architecture of the human MTL along the long axis of the hippocampus and PHG. The hippocampus showed stronger connectivity with striatum, ventral tegmental area and amygdala-regions important for integrating reward and affective signals, whereas the PHG showed stronger connectivity with unimodal and polymodal association cortices. In the hippocampus, the anterior node showed stronger connectivity with the anterior medial temporal lobe and the posterior node showed stronger connectivity with widely distributed cortical and subcortical regions including those involved in sensory and reward processing. In the PHG, differences were characterized by a gradient of increasing anterior-to-posterior connectivity with core nodes of the default mode network. Left and right MTL connectivity patterns were remarkably similar, except for stronger left than right MTL connectivity with regions in the left MTL, the ventral striatum and default mode network. Graph theoretical analysis of MTL-based networks revealed higher node centrality of the posterior, compared to anterior and middle hippocampus. The PHG showed prominent gradients in both node degree and centrality along its anterior-to-posterior axis. Our findings highlight several novel aspects of functional heterogeneity in connectivity along the long axis of the human MTL and provide new insights into how its network organization supports integration and segregation of signals from distributed brain areas. The implications of our findings for a principledunderstanding of distributed pathways that support memory and cognition are discussed.

Abstract

State-space multivariate dynamical systems (MDS) (Ryali et al. 2011) and other causal estimation models are being increasingly used to identify directed functional interactions between brain regions. However, the validity and accuracy of such methods are poorly understood. Performance evaluation based on computer simulations of small artificial causal networks can address this problem to some extent, but they often involve simplifying assumptions that reduce biological validity of the resulting data. Here, we use a novel approach taking advantage of recently developed optogenetic fMRI (ofMRI) techniques to selectively stimulate brain regions while simultaneously recording high-resolution whole-brain fMRI data. ofMRI allows for a more direct investigation of causal influences from the stimulated site to brain regions activated downstream and is therefore ideal for evaluating causal estimation methods in vivo. We used ofMRI to investigate whether MDS models for fMRI can accurately estimate causal functional interactions between brain regions. Two cohorts of ofMRI data were acquired, one at Stanford University and the University of California Los Angeles (Cohort 1) and the other at the University of North Carolina Chapel Hill (Cohort 2). In each cohort, optical stimulation was delivered to the right primary motor cortex (M1). General linear model analysis revealed prominent downstream thalamic activation in Cohort 1, and caudate-putamen (CPu) activation in Cohort 2. MDS accurately estimated causal interactions from M1 to thalamus and from M1 to CPu in Cohort 1 and Cohort 2, respectively. As predicted, no causal influences were found in the reverse direction. Additional control analyses demonstrated the specificity of causal interactions between stimulated and target sites. Our findings suggest that MDS state-space models can accurately and reliably estimate causal interactions in ofMRI data and further validate their use for estimating causal interactions in fMRI. More generally, our study demonstrates that the combined use of optogenetics and fMRI provides a powerful new tool for evaluating computational methods designed to estimate causal interactions between distributed brain regions.

Abstract

Cognitive control plays an important role in goal-directed behavior, but dynamic brain mechanisms underlying it are poorly understood. Here, using multisite fMRI data from over 100 participants, we investigate causal interactions in three cognitive control tasks within a core Frontal-Cingulate-Parietal network. We found significant causal influences from anterior insula (AI) to dorsal anterior cingulate cortex (dACC) in all three tasks. The AI exhibited greater net causal outflow than any other node in the network. Importantly, a similar pattern of causal interactions was uncovered by two different computational methods for causal analysis. Furthermore, the strength of causal interaction from AI to dACC was greater on high, compared with low, cognitive control trials and was significantly correlated with individual differences in cognitive control abilities. These results emphasize the importance of the AI in cognitive control and highlight its role as a causal hub in the Frontal-Cingulate-Parietal network. Our results further suggest that causal signaling between the AI and dACC plays a fundamental role in implementing cognitive control and are consistent with a two-stage cognitive control model in which the AI first detects events requiring greater access to cognitive control resources and then signals the dACC to execute load-specific cognitive control processes.

Distinctive Role of Symbolic Number Sense in Mediating the Mathematical Abilities of Children with AutismJOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERSHiniker, A., Rosenberg-Lee, M., Menon, V.2016; 46 (4): 1268-1281

Abstract

Plasticity of white matter tracts is thought to be essential for cognitive development and academic skill acquisition in children. However, a dearth of high-quality diffusion tensor imaging (DTI) data measuring longitudinal changes with learning, as well as methodological difficulties in multi-time point tract identification have limited our ability to investigate plasticity of specific white matter tracts. Here, we examine learning-related changes of white matter tracts innervating inferior parietal, prefrontal and temporal regions following an intense 2-month math tutoring program. DTI data were acquired from 18 third grade children, both before and after tutoring. A novel fiber tracking algorithm based on a White Matter Query Language (WMQL) was used to identify three sections of the superior longitudinal fasciculus (SLF) linking frontal and parietal (SLF-FP), parietal and temporal (SLF-PT) and frontal and temporal (SLF-FT) cortices, from which we created child-specific probabilistic maps. The SLF-FP, SLF-FT, and SLF-PT tracts identified with the WMQL method were highly reliable across the two time points and showed close correspondence to tracts previously described in adults. Notably, individual differences in behavioral gains after 2 months of tutoring were specifically correlated with plasticity in the left SLF-FT tract. Our results extend previous findings of individual differences in white matter integrity, and provide important new insights into white matter plasticity related to math learning in childhood. More generally, our quantitative approach will be useful for future studies examining longitudinal changes in white matter integrity associated with cognitive skill development.

Distinctive Role of Symbolic Number Sense in Mediating the Mathematical Abilities of Children with Autism.Journal of autism and developmental disordersHiniker, A., Rosenberg-Lee, M., Menon, V.2016; 46 (4): 1268-1281

Abstract

Despite reports of mathematical talent in autism spectrum disorders (ASD), little is known about basic number processing abilities in affected children. We investigated number sense, the ability to rapidly assess quantity information, in 36 children with ASD and 61 typically developing controls. Numerical acuity was assessed using symbolic (Arabic numerals) as well as non-symbolic (dot array) formats. We found significant impairments in non-symbolic acuity in children with ASD, but symbolic acuity was intact. Symbolic acuity mediated the relationship between non-symbolic acuity and mathematical abilities only in children with ASD, indicating a distinctive role for symbolic number sense in the acquisition of mathematical proficiency in this group. Our findings suggest that symbolic systems may help children with ASD organize imprecise information.

Abstract

Cognitive impairments in Parkinson's disease (PD) are thought to be caused in part by dopamine dysregulation. However, even when nigrostriatal dopamine neuron loss is severe enough to cause motor symptoms, many patients remain cognitively unimpaired. It is unclear what brain mechanisms allow these patients to remain cognitively unimpaired despite substantial dopamine dysregulation.31 cognitively unimpaired PD participants OFF dopaminergic-medications were scanned using fMRI while they performed a working memory task, along with 23 controls. We first compared the PD_OFF medication group with controls to determine whether PD participants engage compensatory frontostriatal mechanisms during working memory. We then studied the same PD participants ON dopaminergic-medications to determine whether these compensatory brain changes are altered with dopamine.Controls and PD showed working memory load-dependent activation in the bilateral putamen, anterior-dorsal insula, supplementary motor area, and anterior cingulate cortex. Compared to controls, PD_OFF showed compensatory hyper-activation of bilateral putamen and posterior insula, and machine learning algorithms identified robust differences in putamen activation patterns. Compared to PD_OFF, PD_ON showed reduced compensatory activation in the putamen. Loss of compensatory hyper-activation ON dopaminergic-medication correlated with slower performance on the working memory task and slower cognitive speed on the Symbol Digit Modality Test.Our results provide novel evidence that PD patients maintain normal cognitive performance through compensatory hyper-activation of the putamen. Dopaminergic-medication down-regulates this hyper-activation and the degree of down-regulation predicts behavior. Identifying cognitive compensatory mechanisms in PD is important for understanding how some patients maintain intact cognitive performance, despite nigrostriatal dopamine loss. This article is protected by copyright. All rights reserved.

Abstract

Autism spectrum disorder (ASD) is characterized by reduced attention to salient social stimuli. Here, we use two visual oddball tasks to investigate brain systems engaged during attention to social (face) and non-social (scene) stimuli. We focused on the dorsal and ventral subdivisions of the anterior insula (dAI and vAI, respectively), anatomically distinct regions contributing to a 'salience network' that is known to regulate attention to behaviorally meaningful stimuli. Children with ASD performed comparably to their typically developing (TD) peers, but they engaged the right dAI and vAI differently in response to deviant faces compared with deviant scenes. Multivariate activation patterns in the dAI reliably discriminated between children with ASD and TD children with 85% classification accuracy, and children with ASD activated the vAI more than their TD peers. Children with ASD and their TD peers also differed in dAI connectivity patterns to deviant faces, with stronger within-salience network interactions in the ASD group and stronger cross-network interactions in the TD group. Our findings point to atypical patterns of right anterior insula activation and connectivity in ASD and suggest that multiple functions subserved by the insula, including attention and affective processing of salient social stimuli, are aberrant in children with the disorder.

Abstract

Human cognitive problem solving skills undergo complex experience-dependent changes from childhood to adulthood, yet most neurodevelopmental research has focused on linear changes with age. Here we challenge this limited view, and investigate spatially heterogeneous and nonlinear neurodevelopmental profiles between childhood, adolescence, and young adulthood, focusing on three cytoarchitectonically distinct posterior parietal cortex (PPC) regions implicated in numerical problem solving: intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SMG). Adolescents demonstrated better behavioral performance relative to children, but their performance was equivalent to that of adults. However, all three groups differed significantly in their profile of activation and connectivity across the PPC subdivisions. Activation in bilateral ventral IPS subdivision IPS-hIP1, along with adjoining anterior AG subdivision, AG-PGa, and the posterior SMG subdivision, SMG-PFm, increased linearly with age, whereas the posterior AG subdivision, AG-PGp, was equally deactivated in all three groups. In contrast, the left anterior SMG subdivision, SMG-PF, showed an inverted U-shaped profile across age groups such that adolescents exhibited greater activation than both children and young adults. Critically, greater SMG-PF activation was correlated with task performance only in adolescents. Furthermore, adolescents showed greater task-related functional connectivity of the SMG-PF with ventro-temporal, anterior temporal and prefrontal cortices, relative to both children and adults. These results suggest that nonlinear up-regulation of SMG-PF and its interconnected functional circuits facilitate adult-level performance in adolescents. Our study provides novel insights into heterogeneous age-related maturation of the PPC underlying cognitive skill acquisition, and further demonstrates how anatomically precise analysis of both linear and nonlinear neurofunctional changes with age is necessary for more fully characterizing cognitive development.

Abstract

The Empathizing-Systemizing (E-S) theory describes a profile of traits that have been linked to autism spectrum disorders, and are thought to encompass a continuum that includes typically developing (TD) individuals. Although systemizing is hypothesized to be related to mathematical abilities, empirical support for this relationship is lacking. We examine the link between empathizing and systemizing tendencies and mathematical achievement in 112 TD children (57 girls) to elucidate how socio-cognitive constructs influence early development of mathematical skills. Assessment of mathematical achievement included standardized tests designed to examine calculation skills and conceptual mathematical reasoning. Empathizing and systemizing were assessed using the Combined Empathy Quotient-Child (EQ-C) and Systemizing Quotient-Child (SQ-C). Contrary to our hypothesis, we found that mathematical achievement was not related to systemizing or the discrepancy between systemizing and empathizing. Surprisingly, children with higher empathy demonstrated lower calculation skills. Further analysis using the Social Responsiveness Scale (SRS) revealed that the relationship between EQ-C and mathematical achievement was mediated by social ability rather than autistic behaviors. Finally, social awareness was found to play a differential role in mediating the relationship between EQ-C and mathematical achievement in girls. These results identify empathy, and social skills more generally, as previously unknown predictors of mathematical achievement.

Memory and cognitive control circuits in mathematical cognition and learningMATHEMATICAL BRAIN ACROSS THE LIFESPANMenon, V.2016; 227: 159-186

Abstract

Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed.

Abstract

How the brain develops representations for abstract cognitive problems is a major unaddressed question in neuroscience. Here we tackle this fundamental question using arithmetic problem solving, a cognitive domain important for the development of mathematical reasoning. We first examined whether adults demonstrate common neural representations for addition and subtraction problems, two complementary arithmetic operations that manipulate the same quantities. We then examined how the common neural representations for the two problem types change with development. Whole-brain multivoxel representational similarity (MRS) analysis was conducted to examine common coding of addition and subtraction problems in children and adults. We found that adults exhibited significant levels of MRS between the two problem types, not only in the intraparietal sulcus (IPS) region of the posterior parietal cortex (PPC), but also in ventral temporal-occipital, anterior temporal and dorsolateral prefrontal cortices. Relative to adults, children showed significantly reduced levels of MRS in these same regions. In contrast, no brain areas showed significantly greater MRS between problem types in children. Our findings provide novel evidence that the emergence of arithmetic problem solving skills from childhood to adulthood is characterized by maturation of common neural representations between distinct numerical operations, and involve distributed brain regions important for representing and manipulating numerical quantity. More broadly, our findings demonstrate that representational analysis provides a powerful approach for uncovering fundamental mechanisms by which children develop proficiencies that are a hallmark of human cognition.

Abstract

Developmental dyscalculia (DD) is marked by specific deficits in processing numerical and mathematical information despite normal intelligence (IQ) and reading ability. We examined how brain circuits used by young children with DD to solve simple addition and subtraction problems differ from those used by typically developing (TD) children who were matched on age, IQ, reading ability, and working memory. Children with DD were slower and less accurate during problem solving than TD children, and were especially impaired on their ability to solve subtraction problems. Children with DD showed significantly greater activity in multiple parietal, occipito-temporal and prefrontal cortex regions while solving addition and subtraction problems. Despite poorer performance during subtraction, children with DD showed greater activity in multiple intra-parietal sulcus (IPS) and superior parietal lobule subdivisions in the dorsal posterior parietal cortex as well as fusiform gyrus in the ventral occipito-temporal cortex. Critically, effective connectivity analyses revealed hyper-connectivity, rather than reduced connectivity, between the IPS and multiple brain systems including the lateral fronto-parietal and default mode networks in children with DD during both addition and subtraction. These findings suggest the IPS and its functional circuits are a major locus of dysfunction during both addition and subtraction problem solving in DD, and that inappropriate task modulation and hyper-connectivity, rather than under-engagement and under-connectivity, are the neural mechanisms underlying problem solving difficulties in children with DD. We discuss our findings in the broader context of multiple levels of analysis and performance issues inherent in neuroimaging studies of typical and atypical development.

Abstract

Clustering methods are increasingly employed to segment brain regions into functional subdivisions using resting-state functional magnetic resonance imaging (rs-fMRI). However, these methods are highly sensitive to the (i) precise algorithms employed, (ii) their initializations, and (iii) metrics used for uncovering the optimal number of clusters from the data.To address these issues, we develop a novel consensus clustering evidence accumulation (CC-EAC) framework, which effectively combines multiple clustering methods for segmenting brain regions using rs-fMRI data. Using extensive computer simulations, we examine the performance of widely used clustering algorithms including K-means, hierarchical, and spectral clustering as well as their combinations. We also examine the accuracy and validity of five objective criteria for determining the optimal number of clusters: mutual information, variation of information, modified silhouette, Rand index, and probabilistic Rand index.A CC-EAC framework with a combination of base K-means clustering (KC) and hierarchical clustering (HC) with probabilistic Rand index as the criterion for choosing the optimal number of clusters, accurately uncovered the correct number of clusters from simulated datasets. In experimental rs-fMRI data, these methods reliably detected functional subdivisions of the supplementary motor area, insula, intraparietal sulcus, angular gyrus, and striatum.Unlike conventional approaches, CC-EAC can accurately determine the optimal number of stable clusters in rs-fMRI data, and is robust to initialization and choice of free parameters.A novel CC-EAC framework is proposed for segmenting brain regions, by effectively combining multiple clustering methods and identifying optimal stable functional clusters in rs-fMRI data.

Abstract

Coordinated attention to information from multiple senses is fundamental to our ability to respond to salient environmental events, yet little is known about brain network mechanisms that guide integration of information from multiple senses. Here we investigate dynamic causal mechanisms underlying multisensory auditory-visual attention, focusing on a network of right-hemisphere frontal-cingulate-parietal regions implicated in a wide range of tasks involving attention and cognitive control. Participants performed three 'oddball' attention tasks involving auditory, visual and multisensory auditory-visual stimuli during fMRI scanning. We found that the right anterior insula (rAI) demonstrated the most significant causal influences on all other frontal-cingulate-parietal regions, serving as a major causal control hub during multisensory attention. Crucially, we then tested two competing models of the role of the rAI in multisensory attention: an 'integrated' signaling model in which the rAI generates a common multisensory control signal associated with simultaneous attention to auditory and visual oddball stimuli versus a 'segregated' signaling model in which the rAI generates two segregated and independent signals in each sensory modality. We found strong support for the integrated, rather than the segregated, signaling model. Furthermore, the strength of the integrated control signal from the rAI was most pronounced on the dorsal anterior cingulate and posterior parietal cortices, two key nodes of saliency and central executive networks respectively. These results were preserved with the addition of a superior temporal sulcus region involved in multisensory processing. Our study provides new insights into the dynamic causal mechanisms by which the AI facilitates multisensory attention.

Sex differences in structural organization of motor systems and their dissociable links with repetitive/restricted behaviors in children with autism.Molecular autismSupekar, K., Menon, V.2015; 6: 50-?

Abstract

Autism spectrum disorder (ASD) is diagnosed much less often in females than males. Emerging behavioral accounts suggest that the clinical presentation of autism is different in females and males, yet research examining sex differences in core symptoms of autism in affected children has been limited. Additionally, to date, there have been no systematic attempts to characterize neuroanatomical differences underlying the distinct behavioral profiles observed in girls and boys with ASD. This is in part because extant ASD studies have included a small number of girls.Leveraging the National Database for Autism Research (NDAR), we first analyzed symptom severity in a large sample consisting of 128 ASD girls and 614 age- and IQ-matched ASD boys. We then examined symptom severity and structural imaging data using novel multivariate pattern analysis in a well-matched group of 25 ASD girls, 25 ASD boys, 19 typically developing (TD) girls, and 19 TD boys, obtained from the Autism Brain Imaging Data Exchange (ABIDE).In both the NDAR and ABIDE datasets, girls, compared to boys, with ASD showed less severe repetitive/restricted behaviors (RRBs) and comparable deficits in the social and communication domains. In the ABIDE imaging dataset, gray matter (GM) patterns in the motor cortex, supplementary motor area (SMA), cerebellum, fusiform gyrus, and amygdala accurately discriminated girls and boys with ASD. This sex difference pattern was specific to ASD as the GM in these brain regions did not discriminate TD girls and boys. Moreover, GM in the motor cortex, SMA, and crus 1 subdivision of the cerebellum was correlated with RRB in girls whereas GM in the right putamen-the region that discriminated TD girls and boys-was correlated with RRB in boys.We found robust evidence for reduced levels of RRB in girls, compared to boys, with ASD, providing the strongest evidence to date for sex differences in a core phenotypic feature of childhood ASD. Sex differences in brain morphometry are prominent in the motor system and in areas that comprise the "social brain." Notably, RRB severity is associated with sex differences in GM morphometry in distinct motor regions. Our findings provide novel insights into the neurobiology of sex differences in childhood autism.

Abstract

Male predominance is a prominent feature of autism spectrum disorders (ASD), with a reported male to female ratio of 4:1. Because of the overwhelming focus on males, little is known about the neuroanatomical basis of sex differences in ASD. Investigations of sex differences with adequate sample sizes are critical for improving our understanding of the biological mechanisms underlying ASD in females.We leveraged the open-access autism brain imaging data exchange (ABIDE) dataset to obtain structural brain imaging data from 53 females with ASD, who were matched with equivalent samples of males with ASD, and their typically developing (TD) male and female peers. Brain images were processed with FreeSurfer to assess three key features of local cortical morphometry: volume, thickness, and gyrification. A whole-brain approach was used to identify significant effects of sex, diagnosis, and sex-by-diagnosis interaction, using a stringent threshold of p

Abstract

Although behavioral difficulties are well documented in reading disabilities, little is known about the relationship between math ability and internalizing and externalizing behaviors. Here, we use standardized measures to investigate the relation among early math ability, math anxiety, and internalizing and externalizing behaviors in a group of 366 second and third graders. Math achievement was significantly correlated with attentional difficulties and social problems but not with internalizing symptoms. The relation between math achievement and externalizing behavioral problems was stronger in girls than in boys. Math achievement was not correlated with trait anxiety but was negatively correlated with math anxiety. Critically, math anxiety differed significantly between children classified as math learning disabled (MLD), low achieving (LA), and typically developing (TD), with math anxiety significantly higher in the MLD and LA groups compared to the TD group. Our findings suggest that, even in nonclinical samples, math difficulties at the earliest stages of formal math learning are associated with attentional difficulties and domain-specific anxiety. These findings underscore the need for further examination of the shared cognitive, neural, and genetic influences underlying problem solving and nonverbal learning difficulties and accompanying internalizing and externalizing behaviors.

Abstract

Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during a period in early childhood when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety.We combined structural and functional magnetic resonance imaging with neuropsychological assessments of anxiety based on daily life experiences to investigate the effects of anxiety on the brain in 76 young children. We then used machine learning algorithms with balanced cross-validation to examine brain-based predictors of individual differences in childhood anxiety.Even in children as young as ages 7 to 9, high childhood anxiety is associated with enlarged amygdala volume and this enlargement is localized specifically to the basolateral amygdala. High childhood anxiety is also associated with increased connectivity between the amygdala and distributed brain systems involved in attention, emotion perception, and regulation, and these effects are most prominent in basolateral amygdala. Critically, machine learning algorithms revealed that levels of childhood anxiety could be reliably predicted by amygdala morphometry and intrinsic functional connectivity, with the left basolateral amygdala emerging as the strongest predictor.Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age. Our study provides important new insights into the neurodevelopmental origins of anxiety and has significant implications for the development of predictive biomarkers to identify children at risk for anxiety disorders.

Abstract

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.Molecular Psychiatry advance online publication, 18 June 2013; doi:10.1038/mp.2013.78.

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits. While such deficits have been the focus of most research, recent evidence suggests that individuals with ASD may exhibit cognitive strengths in domains such as mathematics.Cognitive assessments and functional brain imaging were used to investigate mathematical abilities in 18 children with ASD and 18 age-, gender-, and IQ-matched typically developing (TD) children. Multivariate classification and regression analyses were used to investigate whether brain activity patterns during numerical problem solving were significantly different between the groups and predictive of individual mathematical abilities.Children with ASD showed better numerical problem solving abilities and relied on sophisticated decomposition strategies for single-digit addition problems more frequently than TD peers. Although children with ASD engaged similar brain areas as TD children, they showed different multivariate activation patterns related to arithmetic problem complexity in ventral temporal-occipital cortex, posterior parietal cortex, and medial temporal lobe. Furthermore, multivariate activation patterns in ventral temporal-occipital cortical areas typically associated with face processing predicted individual numerical problem solving abilities in children with ASD but not in TD children.Our study suggests that superior mathematical information processing in children with ASD is characterized by a unique pattern of brain organization and that cortical regions typically involved in perceptual expertise may be utilized in novel ways in ASD. Our findings of enhanced cognitive and neural resources for mathematics have critical implications for educational, professional, and social outcomes for individuals with this lifelong disorder.

Abstract

The human brain undergoes protracted developmental changes during which it constructs functional networks that engender complex cognitive abilities. Understanding brain function ultimately depends on knowledge of how dynamic interactions between distributed brain regions mature with age to produce sophisticated cognitive systems. This review summarizes recent progress in our understanding of the ontogeny of functional brain networks. Here I describe how complementary methods for probing functional connectivity are providing unique insights into the emergence and maturation of distinct functional networks from childhood to adulthood. I highlight six emerging principles governing the development of large-scale functional networks and discuss how they inform cognitive and affective function in typically developing children and in children with neurodevelopmental disorders.

Abstract

Intrinsic functional connectivity analysis using resting-state functional magnetic resonance imaging (rsfMRI) has become a powerful tool for examining brain functional organization. Global artifacts such as physiological noise pose a significant problem in estimation of intrinsic functional connectivity. Here we develop and test a novel random subspace method for functional connectivity (RSMFC) that effectively removes global artifacts in rsfMRI data. RSMFC estimates the partial correlation between a seed region and each target brain voxel using multiple subsets of voxels sampled randomly across the whole brain. We evaluated RSMFC on both simulated and experimental rsfMRI data and compared its performance with standard methods that rely on global mean regression (GSReg) which are widely used to remove global artifacts. Using extensive simulations we demonstrate that RSMFC is effective in removing global artifacts in rsfMRI data. Critically, using a novel simulated dataset we demonstrate that, unlike GSReg, RSMFC does not artificially introduce anti-correlations between inherently uncorrelated networks, a result of paramount importance for reliably estimating functional connectivity. Furthermore, we show that the overall sensitivity, specificity and accuracy of RSMFC are superior to GSReg. Analysis of posterior cingulate cortex connectivity in experimental rsfMRI data from 22 healthy adults revealed strong functional connectivity in the default mode network, including more reliable identification of connectivity with left and right medial temporal lobe regions that were missed by GSReg. Notably, compared to GSReg, negative correlations with lateral fronto-parietal regions were significantly weaker in RSMFC. Our results suggest that RSMFC is an effective method for minimizing the effects of global artifacts and artificial negative correlations, while accurately recovering intrinsic functional brain networks.

Abstract

Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show that there are more instances of greater functional connectivity in the brains of children with ASD in comparison to those of typically developing children. Hyperconnectivity in ASD was observed at the whole-brain and subsystems levels, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyperconnectivity predicted symptom severity in ASD, such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain of children with ASD is largely functionally hyperconnected in ways that contribute to social dysfunction. Our findings provide unique insights into brain mechanisms underlying childhood autism.

Abstract

The primary goal of this review is to highlight current research and theories describing the neurobiological basis of math (MD), reading (RD), and comorbid math and reading disability (MD+RD). We first describe the unique brain and cognitive processes involved in acquisition of math and reading skills, emphasizing similarities and differences in each domain. Next we review functional imaging studies of MD and RD in children, integrating relevant theories from experimental psychology and cognitive neuroscience to characterize the functional neuroanatomy of cognitive dysfunction in MD and RD. We then review recent research on the anatomical correlates of MD and RD. Converging evidence from morphometry and tractography studies are presented to highlight distinct patterns of white matter pathways which are disrupted in MD and RD. Finally, we examine how the intersection of MD and RD provides a unique opportunity to clarify the unique and shared brain systems which adversely impact learning and skill acquisition in MD and RD, and point out important areas for future work on comorbid learning disabilities.

Reply to Brock: Renewed focus on the voice and social reward in children with autism.Proceedings of the National Academy of Sciences of the United States of AmericaAbrams, D. A., Uddin, L. Q., Menon, V.2013; 110 (42): E3974-?

Abstract

Anhedonia is the inability to experience pleasure from normally pleasant stimuli. Although anhedonia is a prominent feature of many psychiatric disorders, trait anhedonia is also observed dimensionally in healthy individuals. Currently, the neurobiological basis of anhedonia is poorly understood because it has been mainly investigated in patients with psychiatric disorders. Thus, previous studies have not been able to adequately disentangle the neural correlates of anhedonia from other clinical symptoms. In this study, trait anhedonia was assessed in well-characterized healthy participants with no history of Axis I psychiatric illness. Functional magnetic resonance imaging with musical stimuli was used to examine brain responses and effective connectivity in relation to individual differences in anhedonia. We found that trait anhedonia was negatively correlated with pleasantness ratings of music stimuli and with activation of key brain structures involved in reward processing, including nucleus accumbens (NAc), basal forebrain and hypothalamus which are linked by the medial forebrain bundle to the ventral tegmental area (VTA). Brain regions important for processing salient emotional stimuli, including anterior insula and orbitofrontal cortex were also negatively correlated with trait anhedonia. Furthermore, effective connectivity between NAc, VTA and paralimbic areas, that regulate emotional reactivity to hedonic stimuli, was negatively correlated with trait anhedonia. Our results indicate that trait anhedonia is associated with reduced reactivity and connectivity of mesolimbic and related limbic and paralimbic systems involved in reward processing. Critically, this association can be detected even in individuals without psychiatric illness. Our findings have important implications both for understanding the neurobiological basis of anhedonia and for the treatment of anhedonia in psychiatric disorders.

Abstract

Baddeley and Hitch's multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7-9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development.

Visuo-spatial working memory is an important source of domain-general vulnerability in the development of arithmetic cognition.NeuropsychologiaAshkenazi, S., Rosenberg-Lee, M., Metcalfe, A. W., Swigart, A. G., Menon, V.2013; 51 (11): 2305-2317

Abstract

The study of developmental disorders can provide a unique window into the role of domain-general cognitive abilities and neural systems in typical and atypical development. Mathematical disabilities (MD) are characterized by marked difficulty in mathematical cognition in the presence of preserved intelligence and verbal ability. Although studies of MD have most often focused on the role of core deficits in numerical processing, domain-general cognitive abilities, in particular working memory (WM), have also been implicated. Here we identify specific WM components that are impaired in children with MD and then examine their role in arithmetic problem solving. Compared to typically developing (TD) children, the MD group demonstrated lower arithmetic performance and lower visuo-spatial working memory (VSWM) scores with preserved abilities on the phonological and central executive components of WM. Whole brain analysis revealed that, during arithmetic problem solving, left posterior parietal cortex, bilateral dorsolateral and ventrolateral prefrontal cortex, cingulate gyrus and precuneus, and fusiform gyrus responses were positively correlated with VSWM ability in TD children, but not in the MD group. Additional analyses using a priori posterior parietal cortex regions previously implicated in WM tasks, demonstrated a convergent pattern of results during arithmetic problem solving. These results suggest that MD is characterized by a common locus of arithmetic and VSWM deficits at both the cognitive and functional neuroanatomical levels. Unlike TD children, children with MD do not use VSWM resources appropriately during arithmetic problem solving. This work advances our understanding of VSWM as an important domain-general cognitive process in both typical and atypical mathematical skill development.

Abstract

IMPORTANCE Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood. OBJECTIVES To examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD. DESIGN, SETTING, AND PARTICIPANTS Case-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children. MAIN OUTCOMES AND MEASURES Between-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD. RESULTS We observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual's salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen-level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity. CONCLUSIONS AND RELEVANCE Salience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.

Abstract

BACKGROUND: The default mode network (DMN), a brain system anchored in the posteromedial cortex, has been identified as underconnected in adults with autism spectrum disorder (ASD). However, to date there have been no attempts to characterize this network and its involvement in mediating social deficits in children with ASD. Furthermore, the functionally heterogeneous profile of the posteromedial cortex raises questions regarding how altered connectivity manifests in specific functional modules within this brain region in children with ASD. METHODS: Resting-state functional magnetic resonance imaging and an anatomically informed approach were used to investigate the functional connectivity of the DMN in 20 children with ASD and 19 age-, gender-, and IQ-matched typically developing (TD) children. Multivariate regression analyses were used to test whether altered patterns of connectivity are predictive of social impairment severity. RESULTS: Compared with TD children, children with ASD demonstrated hyperconnectivity of the posterior cingulate and retrosplenial cortices with predominately medial and anterolateral temporal cortex. In contrast, the precuneus in ASD children demonstrated hypoconnectivity with visual cortex, basal ganglia, and locally within the posteromedial cortex. Aberrant posterior cingulate cortex hyperconnectivity was linked with severity of social impairments in ASD, whereas precuneus hypoconnectivity was unrelated to social deficits. Consistent with previous work in healthy adults, a functionally heterogeneous profile of connectivity within the posteromedial cortex in both TD and ASD children was observed. CONCLUSIONS: This work links hyperconnectivity of DMN-related circuits to the core social deficits in young children with ASD and highlights fundamental aspects of posteromedial cortex heterogeneity.

Abstract

Music is a cultural universal and a rich part of the human experience. However, little is known about common brain systems that support the processing and integration of extended, naturalistic 'real-world' music stimuli. We examined this question by presenting extended excerpts of symphonic music, and two pseudomusical stimuli in which the temporal and spectral structure of the Natural Music condition were disrupted, to non-musician participants undergoing functional brain imaging and analysing synchronized spatiotemporal activity patterns between listeners. We found that music synchronizes brain responses across listeners in bilateral auditory midbrain and thalamus, primary auditory and auditory association cortex, right-lateralized structures in frontal and parietal cortex, and motor planning regions of the brain. These effects were greater for natural music compared to the pseudo-musical control conditions. Remarkably, inter-subject synchronization in the inferior colliculus and medial geniculate nucleus was also greater for the natural music condition, indicating that synchronization at these early stages of auditory processing is not simply driven by spectro-temporal features of the stimulus. Increased synchronization during music listening was also evident in a right-hemisphere fronto-parietal attention network and bilateral cortical regions involved in motor planning. While these brain structures have previously been implicated in various aspects of musical processing, our results are the first to show that these regions track structural elements of a musical stimulus over extended time periods lasting minutes. Our results show that a hierarchical distributed network is synchronized between individuals during the processing of extended musical sequences, and provide new insight into the temporal integration of complex and biologically salient auditory sequences.

Abstract

Understanding the organization of the human brain requires identification of its functional subdivisions. Clustering schemes based on resting-state functional magnetic resonance imaging (fMRI) data are rapidly emerging as non-invasive alternatives to cytoarchitectonic mapping in postmortem brains. Here, we propose a novel spatio-temporal probabilistic parcellation scheme that overcomes major weaknesses of existing approaches by (i) modeling the fMRI time series of a voxel as a von Mises-Fisher distribution, which is widely used for clustering high dimensional data; (ii) modeling the latent cluster labels as a Markov random field, which provides spatial regularization on the cluster labels by penalizing neighboring voxels having different cluster labels; and (iii) introducing a prior on the number of labels, which helps in uncovering the number of clusters automatically from the data. Cluster labels and model parameters are estimated by an iterative expectation maximization procedure wherein, given the data and current estimates of model parameters, the latent cluster labels, are computed using α-expansion, a state of the art graph cut, method. In turn, given the current estimates of cluster labels, model parameters are estimated by maximizing the pseudo log-likelihood. The performance of the proposed method is validated using extensive computer simulations. Using novel stability analysis we examine the sensitivity of our methods to parameter initialization and demonstrate that the method is robust to a wide range of initial parameter values. We demonstrate the application of our methods by parcellating spatially contiguous as well as non-contiguous brain regions at both the individual participant and group levels. Notably, our analyses yield new data on the posterior boundaries of the supplementary motor area and provide new insights into functional organization of the insular cortex. Taken together, our findings suggest that our method is a powerful tool for investigating functional subdivisions in the human brain.

Abstract

While there is almost universal agreement amongst researchers that autism is associated with alterations in brain connectivity, the precise nature of these alterations continues to be debated. Theoretical and empirical work is beginning to reveal that autism is associated with a complex functional phenotype characterized by both hypo- and hyper-connectivity of large-scale brain systems. It is not yet understood why such conflicting patterns of brain connectivity are observed across different studies, and the factors contributing to these heterogeneous findings have not been identified. Developmental changes in functional connectivity have received inadequate attention to date. We propose that discrepancies between findings of autism related hypo-connectivity and hyper-connectivity might be reconciled by taking developmental changes into account. We review neuroimaging studies of autism, with an emphasis on functional magnetic resonance imaging studies of intrinsic functional connectivity in children, adolescents and adults. The consistent pattern emerging across several studies is that while intrinsic functional connectivity in adolescents and adults with autism is generally reduced compared with age-matched controls, functional connectivity in younger children with the disorder appears to be increased. We suggest that by placing recent empirical findings within a developmental framework, and explicitly characterizing age and pubertal stage in future work, it may be possible to resolve conflicting findings of hypo- and hyper-connectivity in the extant literature and arrive at a more comprehensive understanding of the neurobiology of autism.

Reply to Brock: Renewed focus on the voice and social reward in children with autismProceedings of the National Academy of Sciences of the United States of AmericaAbrams, D. A., Uddin, L. Q., Menon, V.2013

Abstract

Focused hypnotic concentration is a model for brain control over sensation and behavior. Pain and anxiety can be effectively alleviated by hypnotic suggestion, which modulates activity in brain regions associated with focused attention, but the specific neural network underlying this phenomenon is not known.To investigate the brain basis of hypnotizability.Cross-sectional, in vivo neuroimaging study performed from November 2005 through July 2006.Academic medical center at Stanford University School of Medicine.Twelve adults with high and 12 adults with low hypnotizability.Functional magnetic resonance imaging to measure functional connectivity networks at rest, including default-mode, salience, and executive-control networks; structural T1 magnetic resonance imaging to measure regional gray and white matter volumes; and diffusion tensor imaging to measure white matter microstructural integrity.High compared with low hypnotizable individuals had greater functional connectivity between the left dorsolateral prefrontal cortex, an executive-control region of the brain, and the salience network composed of the dorsal anterior cingulate cortex, anterior insula, amygdala, and ventral striatum, involved in detecting, integrating, and filtering relevant somatic, autonomic, and emotional information using independent component analysis. Seed-based analysis confirmed elevated functional coupling between the dorsal anterior cingulate cortex and the dorsolateral prefrontal cortex in high compared with low hypnotizable individuals. These functional differences were not due to any variation in brain structure in these regions, including regional gray and white matter volumes and white matter microstructure.Our results provide novel evidence that altered functional connectivity in the dorsolateral prefrontal cortex and dorsal anterior cingulate cortex may underlie hypnotizability. Future studies focusing on how these functional networks change and interact during hypnosis are warranted.

Abstract

Children's gains in problem-solving skills during the elementary school years are characterized by shifts in the mix of problem-solving approaches, with inefficient procedural strategies being gradually replaced with direct retrieval of domain-relevant facts. We used a well-established procedure for strategy assessment during arithmetic problem solving to investigate the neural basis of this critical transition. We indexed behavioral strategy use by focusing on the retrieval frequency and examined changes in brain activity and connectivity associated with retrieval fluency during arithmetic problem solving in second- and third-grade (7- to 9-year-old) children. Children with higher retrieval fluency showed elevated signal in the right hippocampus, parahippocampal gyrus (PHG), lingual gyrus (LG), fusiform gyrus (FG), left ventrolateral PFC (VLPFC), bilateral dorsolateral PFC (DLPFC), and posterior angular gyrus. Critically, these effects were not confounded by individual differences in problem-solving speed or accuracy. Psychophysiological interaction analysis revealed significant effective connectivity of the right hippocampus with bilateral VLPFC and DLPFC during arithmetic problem solving. Dynamic causal modeling analysis revealed strong bidirectional interactions between the hippocampus and the left VLPFC and DLPFC. Furthermore, causal influences from the left VLPFC to the hippocampus served as the main top-down component, whereas causal influences from the hippocampus to the left DLPFC served as the main bottom-up component of this retrieval network. Our study highlights the contribution of hippocampal-prefrontal circuits to the early development of retrieval fluency in arithmetic problem solving and provides a novel framework for studying dynamic developmental processes that accompany children's development of problem-solving skills.

Abstract

Math anxiety is a negative emotional reaction to situations involving mathematical problem solving. Math anxiety has a detrimental impact on an individual's long-term professional success, but its neurodevelopmental origins are unknown. In a functional MRI study on 7- to 9-year-old children, we showed that math anxiety was associated with hyperactivity in right amygdala regions that are important for processing negative emotions. In addition, we found that math anxiety was associated with reduced activity in posterior parietal and dorsolateral prefrontal cortex regions involved in mathematical reasoning. Multivariate classification analysis revealed distinct multivoxel activity patterns, which were independent of overall activation levels in the right amygdala. Furthermore, effective connectivity between the amygdala and ventromedial prefrontal cortex regions that regulate negative emotions was elevated in children with math anxiety. These effects were specific to math anxiety and unrelated to general anxiety, intelligence, working memory, or reading ability. Our study identified the neural correlates of math anxiety for the first time, and our findings have significant implications for its early identification and treatment.

Abstract

Characterizing interactions between multiple brain regions is important for understanding brain function. Functional connectivity measures based on partial correlation provide an estimate of the linear conditional dependence between brain regions after removing the linear influence of other regions. Estimation of partial correlations is, however, difficult when the number of regions is large, as is now increasingly the case with a growing number of large-scale brain connectivity studies. To address this problem, we develop novel methods for estimating sparse partial correlations between multiple regions in fMRI data using elastic net penalty (SPC-EN), which combines L1- and L2-norm regularization We show that L1-norm regularization in SPC-EN provides sparse interpretable solutions while L2-norm regularization improves the sensitivity of the method when the number of possible connections between regions is larger than the number of time points, and when pair-wise correlations between brain regions are high. An issue with regularization-based methods is choosing the regularization parameters which in turn determine the selection of connections between brain regions. To address this problem, we deploy novel stability selection methods to infer significant connections between brain regions. We also compare the performance of SPC-EN with existing methods which use only L1-norm regularization (SPC-L1) on simulated and experimental datasets. Detailed simulations show that the performance of SPC-EN, measured in terms of sensitivity and accuracy is superior to SPC-L1, especially at higher rates of feature prevalence. Application of our methods to resting-state fMRI data obtained from 22 healthy adults shows that SPC-EN reveals a modular architecture characterized by strong inter-hemispheric links, distinct ventral and dorsal stream pathways, and a major hub in the posterior medial cortex - features that were missed by conventional methods. Taken together, our findings suggest that SPC-EN provides a powerful tool for characterizing connectivity involving a large number of correlated regions that span the entire brain.

Abstract

Developmental dyscalculia (DD) is a disability that impacts math learning and skill acquisition in school-age children. Here we investigate arithmetic problem solving deficits in young children with DD using univariate and multivariate analysis of fMRI data. During fMRI scanning, 17 children with DD (ages 7-9, grades 2 and 3) and 17 IQ- and reading ability-matched typically developing (TD) children performed complex and simple addition problems which differed only in arithmetic complexity. While the TD group showed strong modulation of brain responses with increasing arithmetic complexity, children with DD failed to show such modulation. Children with DD showed significantly reduced activation compared to TD children in the intraparietal sulcus, superior parietal lobule, supramarginal gyrus and bilateral dorsolateral prefrontal cortex in relation to arithmetic complexity. Critically, multivariate representational similarity revealed that brain response patterns to complex and simple problems were less differentiated in the DD group in bilateral anterior IPS, independent of overall differences in signal level. Taken together, these results show that children with DD not only under-activate key brain regions implicated in mathematical cognition, but they also fail to generate distinct neural responses and representations for different arithmetic problems. Our findings provide novel insights into the neural basis of DD.

Abstract

Unlike natural numbers, negative numbers do not have natural physical referents. How does the brain represent such abstract mathematical concepts? Two competing hypotheses regarding representational systems for negative numbers are a rule-based model, in which symbolic rules are applied to negative numbers to translate them into positive numbers when assessing magnitudes, and an expanded magnitude model, in which negative numbers have a distinct magnitude representation. Using an event-related functional magnetic resonance imaging design, we examined brain responses in 22 adults while they performed magnitude comparisons of negative and positive numbers that were quantitatively near (difference <4) or far apart (difference >6). Reaction times (RTs) for negative numbers were slower than positive numbers, and both showed a distance effect whereby near pairs took longer to compare. A network of parietal, frontal, and occipital regions were differentially engaged by negative numbers. Specifically, compared to positive numbers, negative number processing resulted in greater activation bilaterally in intraparietal sulcus (IPS), middle frontal gyrus, and inferior lateral occipital cortex. Representational similarity analysis revealed that neural responses in the IPS were more differentiated among positive numbers than among negative numbers, and greater differentiation among negative numbers was associated with faster RTs. Our findings indicate that despite negative numbers engaging the IPS more strongly, the underlying neural representation are less distinct than that of positive numbers. We discuss our findings in the context of the two theoretical models of negative number processing and demonstrate how multivariate approaches can provide novel insights into abstract number representation.

Abstract

Decoding specific cognitive states from brain activity constitutes a major goal of neuroscience. Previous studies of brain-state classification have focused largely on decoding brief, discrete events and have required the timing of these events to be known. To date, methods for decoding more continuous and purely subject-driven cognitive states have not been available. Here, we demonstrate that free-streaming subject-driven cognitive states can be decoded using a novel whole-brain functional connectivity analysis. Ninety functional regions of interest (ROIs) were defined across 14 large-scale resting-state brain networks to generate a 3960 cell matrix reflecting whole-brain connectivity. We trained a classifier to identify specific patterns of whole-brain connectivity as subjects rested quietly, remembered the events of their day, subtracted numbers, or (silently) sang lyrics. In a leave-one-out cross-validation, the classifier identified these 4 cognitive states with 84% accuracy. More critically, the classifier achieved 85% accuracy when identifying these states in a second, independent cohort of subjects. Classification accuracy remained high with imaging runs as short as 30-60 s. At all temporal intervals assessed, the 90 functionally defined ROIs outperformed a set of 112 commonly used structural ROIs in classifying cognitive states. This approach should enable decoding a myriad of subject-driven cognitive states from brief imaging data samples.

Abstract

Although the detrimental effects of math anxiety in adults are well understood, few studies have examined how it affects younger children who are beginning to learn math in a formal academic setting. Here, we examine the relationship between math anxiety and math achievement in second and third graders. In response to the need for a grade-appropriate measure of assessing math anxiety in this group we first describe the development of Scale for Early Mathematics Anxiety (SEMA), a new measure for assessing math anxiety in second and third graders that is based on the Math Anxiety Rating Scale. We demonstrate the construct validity and reliability of the SEMA and use it to characterize the effect of math anxiety on standardized measures of math abilities, as assessed using the Mathematical Reasoning and Numerical Operations subtests of the Wechsler Individual Achievement Test (WIAT-II). Math achievement, as measured by the WIAT-II Math Composite score, was significantly and negatively correlated with SEMA but not with trait anxiety scores. Additional analyses showed that SEMA scores were strongly correlated with Mathematical Reasoning scores, which involves more complex verbal problem solving. SEMA scores were weakly correlated with Numerical Operations which assesses basic computation skills, suggesting that math anxiety has a pronounced effect on more demanding calculations. We also found that math anxiety has an equally detrimental impact on math achievement regardless of whether children have an anxiety related to numbers or to the situational and social experience of doing math. Critically, these effects were unrelated to trait anxiety, providing the first evidence that the specific effects of math anxiety can be detected in the earliest stages of formal math learning in school. Our findings provide new insights into the developmental origins of math anxiety, and further underscore the need to remediate math anxiety and its deleterious effects on math achievement in young children.

Abstract

Autism spectrum disorders (ASD) are neurodevelopmental disorders with a prevalence of nearly 1:100. Structural imaging studies point to disruptions in multiple brain areas, yet the precise neuroanatomical nature of these disruptions remains unclear. Characterization of brain structural differences in children with ASD is critical for development of biomarkers that may eventually be used to improve diagnosis and monitor response to treatment.We use voxel-based morphometry along with a novel multivariate pattern analysis approach and searchlight algorithm to classify structural magnetic resonance imaging data acquired from 24 children and adolescents with autism and 24 age-, gender-, and IQ-matched neurotypical participants.Despite modest voxel-based morphometry differences, multivariate pattern analysis revealed that the groups could be distinguished with accuracies of approximately 90% based on gray matter in the posterior cingulate cortex, medial prefrontal cortex, and bilateral medial temporal lobes-regions within the default mode network. Abnormalities in the posterior cingulate cortex were associated with impaired Autism Diagnostic Interview communication scores. Gray matter in additional prefrontal, lateral temporal, and subcortical structures also discriminated between groups with accuracies between 81% and 90%. White matter in the inferior fronto-occipital and superior longitudinal fasciculi, and the genu and splenium of the corpus callosum, achieved up to 85% classification accuracy.Multiple brain regions, including those belonging to the default mode network, exhibit aberrant structural organization in children with autism. Brain-based biomarkers derived from structural magnetic resonance imaging data may contribute to identification of the neuroanatomical basis of symptom heterogeneity and to the development of targeted early interventions.

Abstract

Cognitive development and learning are characterized by diminished reliance on effortful procedures and increased use of memory-based problem solving. Here we identify the neural correlates of this strategy shift in 7-9-year-old children at an important developmental period for arithmetic skill acquisition. Univariate and multivariate approaches were used to contrast brain responses between two groups of children who relied primarily on either retrieval or procedural counting strategies. Children who used retrieval strategies showed greater responses in the left ventrolateral prefrontal cortex; notably, this was the only brain region which showed univariate differences in signal intensity between the two groups. In contrast, multivariate analysis revealed distinct multivoxel activity patterns in bilateral hippocampus, posterior parietal cortex and left ventrolateral prefrontal cortex regions between the two groups. These results demonstrate that retrieval and counting strategies during early learning are characterized by distinct patterns of activity in a distributed network of brain regions involved in arithmetic problem solving and controlled retrieval of arithmetic facts. Our findings suggest that the reorganization and refinement of neural activity patterns in multiple brain regions plays a dominant role in the transition to memory-based arithmetic problem solving. Our findings further demonstrate how multivariate approaches can provide novel insights into fine-scale developmental changes in the brain. More generally, our study illustrates how brain imaging and developmental research can be integrated to investigate fundamental aspects of neurocognitive development.

What difference does a year of schooling make? Maturation of brain response and connectivity between 2nd and 3rd grades during arithmetic problem solvingNEUROIMAGERosenberg-Lee, M., Barth, M., Menon, V.2011; 57 (3): 796-808

Abstract

Early elementary schooling in 2nd and 3rd grades (ages 7-9) is an important period for the acquisition and mastery of basic mathematical skills. Yet, we know very little about neurodevelopmental changes that might occur over a year of schooling. Here we examine behavioral and neurodevelopmental changes underlying arithmetic problem solving in a well-matched group of 2nd (n = 45) and 3rd (n = 45) grade children. Although 2nd and 3rd graders did not differ on IQ or grade- and age-normed measures of math, reading and working memory, 3rd graders had higher raw math scores (effect sizes = 1.46-1.49) and were more accurate than 2nd graders in an fMRI task involving verification of simple and complex two-operand addition problems (effect size = 0.43). In both 2nd and 3rd graders, arithmetic complexity was associated with increased responses in right inferior frontal sulcus and anterior insula, regions implicated in domain-general cognitive control, and in left intraparietal sulcus (IPS) and superior parietal lobule (SPL) regions important for numerical and arithmetic processing. Compared to 2nd graders, 3rd graders showed greater activity in dorsal stream parietal areas right SPL, IPS and angular gyrus (AG) as well as ventral visual stream areas bilateral lingual gyrus (LG), right lateral occipital cortex (LOC) and right parahippocampal gyrus (PHG). Significant differences were also observed in the prefrontal cortex (PFC), with 3rd graders showing greater activation in left dorsal lateral PFC (dlPFC) and greater deactivation in the ventral medial PFC (vmPFC). Third graders also showed greater functional connectivity between the left dlPFC and multiple posterior brain areas, with larger differences in dorsal stream parietal areas SPL and AG, compared to ventral stream visual areas LG, LOC and PHG. No such between-grade differences were observed in functional connectivity between the vmPFC and posterior brain regions. These results suggest that even the narrow one-year interval spanning grades 2 and 3 is characterized by significant arithmetic task-related changes in brain response and connectivity, and argue that pooling data across wide age ranges and grades can miss important neurodevelopmental changes. Our findings have important implications for understanding brain mechanisms mediating early maturation of mathematical skills and, more generally, for educational neuroscience.

Abstract

Music and speech are complex sound streams with hierarchical rules of temporal organization that become elaborated over time. Here, we use functional magnetic resonance imaging to measure brain activity patterns in 20 right-handed nonmusicians as they listened to natural and temporally reordered musical and speech stimuli matched for familiarity, emotion, and valence. Heart rate variability and mean respiration rates were simultaneously measured and were found not to differ between musical and speech stimuli. Although the same manipulation of temporal structure elicited brain activation level differences of similar magnitude for both music and speech stimuli, multivariate classification analysis revealed distinct spatial patterns of brain responses in the 2 domains. Distributed neuronal populations that included the inferior frontal cortex, the posterior and anterior superior and middle temporal gyri, and the auditory brainstem classified temporal structure manipulations in music and speech with significant levels of accuracy. While agreeing with previous findings that music and speech processing share neural substrates, this work shows that temporal structure in the 2 domains is encoded differently, highlighting a fundamental dissimilarity in how the same neural resources are deployed.

Abstract

Although lesion studies over the past several decades have focused on functional dissociations in posterior parietal cortex (PPC) during arithmetic, no consistent view has emerged of its differential involvement in addition, subtraction, multiplication, and division. To circumvent problems with poor anatomical localization, we examined functional overlap and dissociations in cytoarchitectonically defined subdivisions of the intraparietal sulcus (IPS), superior parietal lobule (SPL) and angular gyrus (AG), across these four operations. Compared to a number identification control task, all operations except addition, showed a consistent profile of left posterior IPS activation and deactivation in the right posterior AG. Multiplication and subtraction differed significantly in right, but not left, IPS and AG activity, challenging the view that the left AG differentially subserves retrieval during multiplication. Although addition and multiplication both rely on retrieval, multiplication evoked significantly greater activation in right posterior IPS, as well as the prefrontal cortex, lingual and fusiform gyri, demonstrating that addition and multiplication engage different brain processes. Comparison of PPC responses to the two pairs of inverse operations: division versus multiplication and subtraction versus addition revealed greater activation of left lateral SPL during division, suggesting that processing inverse relations is operation specific. Our findings demonstrate that individual IPS, SPL and AG subdivisions are differentially modulated by the four arithmetic operations and they point to significant functional heterogeneity and individual differences in activation and deactivation within the PPC. Critically, these effects are related to retrieval, calculation and inversion, the three key cognitive processes that are differentially engaged by arithmetic operations. Our findings point to distribute representation of these processes in the human PPC and also help explain why lesion and previous imaging studies have yielded inconsistent findings.

Abstract

The electrophysiological basis for higher brain activity during rest and internally directed cognition within the human default mode network (DMN) remains largely unknown. Here we use intracranial recordings in the human posteromedial cortex (PMC), a core node within the DMN, during conditions of cued rest, autobiographical judgments, and arithmetic processing. We found a heterogeneous profile of PMC responses in functional, spatial, and temporal domains. Although the majority of PMC sites showed increased broad gamma band activity (30-180 Hz) during rest, some PMC sites, proximal to the retrosplenial cortex, responded selectively to autobiographical stimuli. However, no site responded to both conditions, even though they were located within the boundaries of the DMN identified with resting-state functional imaging and similarly deactivated during arithmetic processing. These findings, which provide electrophysiological evidence for heterogeneity within the core of the DMN, will have important implications for neuroimaging studies of the DMN.

Abstract

Analysis of dynamical interactions between distributed brain areas is of fundamental importance for understanding cognitive information processing. However, estimating dynamic causal interactions between brain regions using functional magnetic resonance imaging (fMRI) poses several unique challenges. For one, fMRI measures Blood Oxygenation Level Dependent (BOLD) signals, rather than the underlying latent neuronal activity. Second, regional variations in the hemodynamic response function (HRF) can significantly influence estimation of causal interactions between them. Third, causal interactions between brain regions can change with experimental context over time. To overcome these problems, we developed a novel state-space Multivariate Dynamical Systems (MDS) model to estimate intrinsic and experimentally-induced modulatory causal interactions between multiple brain regions. A probabilistic graphical framework is then used to estimate the parameters of MDS as applied to fMRI data. We show that MDS accurately takes into account regional variations in the HRF and estimates dynamic causal interactions at the level of latent signals. We develop and compare two estimation procedures using maximum likelihood estimation (MLE) and variational Bayesian (VB) approaches for inferring model parameters. Using extensive computer simulations, we demonstrate that, compared to Granger causal analysis (GCA), MDS exhibits superior performance for a wide range of signal to noise ratios (SNRs), sample length and network size. Our simulations also suggest that GCA fails to uncover causal interactions when there is a conflict between the direction of intrinsic and modulatory influences. Furthermore, we show that MDS estimation using VB methods is more robust and performs significantly better at low SNRs and shorter time series than MDS with MLE. Our study suggests that VB estimation of MDS provides a robust method for estimating and interpreting causal network interactions in fMRI data.

Abstract

The inferior parietal lobule (IPL) of the human brain is a heterogeneous region involved in visuospatial attention, memory, and mathematical cognition. Detailed description of connectivity profiles of subdivisions within the IPL is critical for accurate interpretation of functional neuroimaging studies involving this region. We separately examined functional and structural connectivity of the angular gyrus (AG) and the intraparietal sulcus (IPS) using probabilistic cytoarchitectonic maps. Regions-of-interest (ROIs) included anterior and posterior AG subregions (PGa, PGp) and 3 IPS subregions (hIP2, hIP1, and hIP3). Resting-state functional connectivity analyses showed that PGa was more strongly linked to basal ganglia, ventral premotor areas, and ventrolateral prefrontal cortex, while PGp was more strongly connected with ventromedial prefrontal cortex, posterior cingulate, and hippocampus-regions comprising the default mode network. The anterior-most IPS ROIs, hIP2 and hIP1, were linked with ventral premotor and middle frontal gyrus, while the posterior-most IPS ROI, hIP3, showed connectivity with extrastriate visual areas. In addition, hIP1 was connected with the insula. Tractography using diffusion tensor imaging revealed structural connectivity between most of these functionally connected regions. Our findings provide evidence for functional heterogeneity of cytoarchitectonically defined subdivisions within IPL and offer a novel framework for synthesis and interpretation of the task-related activations and deactivations involving the IPL during cognition.

Abstract

Functional and structural maturation of networks comprised of discrete regions is an important aspect of brain development. The default-mode network (DMN) is a prominent network which includes the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), medial temporal lobes (MTL), and angular gyrus (AG). Despite increasing interest in DMN function, little is known about its maturation from childhood to adulthood. Here we examine developmental changes in DMN connectivity using a multimodal imaging approach by combining resting-state fMRI, voxel-based morphometry and diffusion tensor imaging-based tractography. We found that the DMN undergoes significant developmental changes in functional and structural connectivity, but these changes are not uniform across all DMN nodes. Convergent structural and functional connectivity analyses suggest that PCC-mPFC connectivity along the cingulum bundle is the most immature link in the DMN of children. Both PCC and mPFC also showed gray matter volume differences, as well as prominent macrostructural and microstructural differences in the dorsal cingulum bundle linking these regions. Notably, structural connectivity between PCC and left MTL was either weak or non-existent in children, even though functional connectivity did not differ from that of adults. These results imply that functional connectivity in children can reach adult-like levels despite weak structural connectivity. We propose that maturation of PCC-mPFC structural connectivity plays an important role in the development of self-related and social-cognitive functions that emerge during adolescence. More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks.

Abstract

Multivariate pattern recognition methods are increasingly being used to identify multiregional brain activity patterns that collectively discriminate one cognitive condition or experimental group from another, using fMRI data. The performance of these methods is often limited because the number of regions considered in the analysis of fMRI data is large compared to the number of observations (trials or participants). Existing methods that aim to tackle this dimensionality problem are less than optimal because they either over-fit the data or are computationally intractable. Here, we describe a novel method based on logistic regression using a combination of L1 and L2 norm regularization that more accurately estimates discriminative brain regions across multiple conditions or groups. The L1 norm, computed using a fast estimation procedure, ensures a fast, sparse and generalizable solution; the L2 norm ensures that correlated brain regions are included in the resulting solution, a critical aspect of fMRI data analysis often overlooked by existing methods. We first evaluate the performance of our method on simulated data and then examine its effectiveness in discriminating between well-matched music and speech stimuli. We also compared our procedures with other methods which use either L1-norm regularization alone or support vector machine-based feature elimination. On simulated data, our methods performed significantly better than existing methods across a wide range of contrast-to-noise ratios and feature prevalence rates. On experimental fMRI data, our methods were more effective in selectively isolating a distributed fronto-temporal network that distinguished between brain regions known to be involved in speech and music processing. These findings suggest that our method is not only computationally efficient, but it also achieves the twin objectives of identifying relevant discriminative brain regions and accurately classifying fMRI data.

Abstract

The insula is a brain structure implicated in disparate cognitive, affective, and regulatory functions, including interoceptive awareness, emotional responses, and empathic processes. While classically considered a limbic region, recent evidence from network analysis suggests a critical role for the insula, particularly the anterior division, in high-level cognitive control and attentional processes. The crucial insight and view we present here is of the anterior insula as an integral hub in mediating dynamic interactions between other large-scale brain networks involved in externally oriented attention and internally oriented or self-related cognition. The model we present postulates that the insula is sensitive to salient events, and that its core function is to mark such events for additional processing and initiate appropriate control signals. The anterior insula and the anterior cingulate cortex form a "salience network" that functions to segregate the most relevant among internal and extrapersonal stimuli in order to guide behavior. Within the framework of our network model, the disparate functions ascribed to the insula can be conceptualized by a few basic mechanisms: (1) bottom-up detection of salient events, (2) switching between other large-scale networks to facilitate access to attention and working memory resources when a salient event is detected, (3) interaction of the anterior and posterior insula to modulate autonomic reactivity to salient stimuli, and (4) strong functional coupling with the anterior cingulate cortex that facilitates rapid access to the motor system. In this manner, with the insula as its integral hub, the salience network assists target brain regions in the generation of appropriate behavioral responses to salient stimuli. We suggest that this framework provides a parsimonious account of insula function in neurotypical adults, and may provide novel insights into the neural basis of disorders of affective and social cognition.

Abstract

Clinical data suggest that abnormalities in the regulation of emotional processing contribute to the pathophysiology of generalized anxiety disorder, yet these abnormalities remain poorly understood at the neurobiological level. The authors recently reported that in healthy volunteers the pregenual anterior cingulate regulates emotional conflict on a trial-by-trial basis by dampening activity in the amygdala. The authors also showed that this process is specific to the regulation of emotional, compared to nonemotional, conflict. Here the authors examined whether this form of noninstructed emotion regulation is perturbed in generalized anxiety disorder.Seventeen patients with generalized anxiety disorder and 24 healthy comparison subjects underwent functional MRI while performing an emotional conflict task that involved categorizing facial affect while ignoring overlaid affect label words. Behavioral and neural measures were used to compare trial-by-trial changes in conflict regulation.Comparison subjects effectively regulated emotional conflict from trial to trial, even though they were unaware of having done so. By contrast, patients with generalized anxiety disorder were completely unable to regulate emotional conflict and failed to engage the pregenual anterior cingulate in ways that would dampen amygdalar activity. Moreover, performance and brain activation were correlated with symptoms and could be used to accurately classify the two groups.These data demonstrate that patients with generalized anxiety disorder show significant deficits in the noninstructed and spontaneous regulation of emotional processing. Conceptualization of anxiety as importantly involving abnormalities in emotion regulation, particularly a type occurring outside of awareness, may open up avenues for novel treatments, such as by targeting the medial prefrontal cortex.

Abstract

The contribution of the three core components of working memory (WM) to the development of mathematical skills in young children is poorly understood. The relation between specific WM components and Numerical Operations, which emphasize computation and fact retrieval, and Mathematical Reasoning, which emphasizes verbal problem solving abilities in 48 2nd and 50 3rd graders was assessed using standardized WM and mathematical achievement measures. For 2nd graders, the central executive and phonological components predicted Mathematical Reasoning skills; whereas the visuo-spatial component predicted both Mathematical Reasoning and Numerical Operations skills in 3rd graders. This pattern suggests that the central executive and phonological loop facilitate performance during early stages of mathematical learning whereas visuo-spatial representations play an increasingly important role during later stages. We propose that these changes reflect a shift from prefrontal to parietal cortical functions during mathematical skill acquisition. Implications for learning and individual differences are discussed.

Abstract

We investigated the neural basis of repetition priming (RP) during mathematical cognition. Previous studies of RP have focused on repetition suppression as the basis of behavioral facilitation, primarily using word and object identification and classification tasks. More recently, researchers have suggested associative stimulus-response learning as an alternate model for behavioral facilitation. We examined the neural basis of RP during mathematical problem solving in the context of these two models of learning. Brain imaging and behavioral data were acquired from 39 adults during novel and repeated presentation of three-operand mathematical equations. Despite wide-spread decreases in activation during repeat, compared with novel trials, there was no direct relation between behavioral facilitation and the degree of repetition suppression in any brain region. Rather, RT improvements were directly correlated with repetition enhancement in the hippocampus and the posteromedial cortex [posterior cingulate cortex, precuneus, and retrosplenial cortex; Brodmann's areas (BAs) 23, 7, and 30, respectively], regions known to support memory formation and retrieval, and in the SMA (BA 6) and the dorsal midcingulate ("motor cingulate") cortex (BA 24d), regions known to be important for motor learning. Furthermore, improvements in RT were also correlated with increased functional connectivity of the hippocampus with both the SMA and the dorsal midcingulate cortex. Our findings provide novel support for the hypothesis that repetition enhancement and associated stimulus-response learning may facilitate behavioral performance during problem solving.

Developmental cognitive neuroscience of arithmetic: implications for learning and education.ZDM : the international journal on mathematics education2010; 42 (6): 515–25

Abstract

In this article, we review the brain and cognitive processes underlying the development of arithmetic skills. This review focuses primarily on the development of arithmetic skills in children, but it also summarizes relevant findings from adults for which a larger body of research currently exists. We integrate relevant findings and theories from experimental psychology and cognitive neuroscience. We describe the functional neuroanatomy of cognitive processes that influence and facilitate arithmetic skill development, including calculation, retrieval, strategy use, decision making, as well as working memory and attention. Building on recent findings from functional brain imaging studies, we describe the role of distributed brain regions in the development of mathematical skills. We highlight neurodevelopmental models that go beyond the parietal cortex role in basic number processing, in favor of multiple neural systems and pathways involved in mathematical information processing. From this viewpoint, we outline areas for future study that may help to bridge the gap between the cognitive neuroscience of arithmetic skill development and educational practice.

Abstract

Over the past several decades, structural MRI studies have provided remarkable insights into human brain development by revealing the trajectory of gray and white matter maturation from childhood to adolescence and adulthood. In parallel, functional MRI studies have demonstrated changes in brain activation patterns accompanying cognitive development. Despite these advances, studying the maturation of functional brain networks underlying brain development continues to present unique scientific and methodological challenges. Resting-state fMRI (rsfMRI) has emerged as a novel method for investigating the development of large-scale functional brain networks in infants and young children. We review existing rsfMRI developmental studies and discuss how this method has begun to make significant contributions to our understanding of maturing brain organization. In particular, rsfMRI has been used to complement studies in other modalities investigating the emergence of functional segregation and integration across short and long-range connections spanning the entire brain. We show that rsfMRI studies help to clarify and reveal important principles of functional brain development, including a shift from diffuse to focal activation patterns, and simultaneous pruning of local connectivity and strengthening of long-range connectivity with age. The insights gained from these studies also shed light on potentially disrupted functional networks underlying atypical cognitive development associated with neurodevelopmental disorders. We conclude by identifying critical gaps in the current literature, discussing methodological issues, and suggesting avenues for future research.

Abstract

Although the inferior parietal cortex (IPC) has been consistently implicated in mathematical cognition, the functional roles of its subdivisions are poorly understood. We address this problem using probabilistic cytoarchitectonic maps of IPC subdivisions intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus. We quantified IPC responses relative to task difficulty and individual differences in task proficiency during mental arithmetic (MA) tasks performed with Arabic (MA-A) and Roman (MA-R) numerals. The 2 tasks showed similar levels of activation in 3 distinct IPS areas, hIP1, hIP2, and hIP3, suggesting their obligatory role in MA. Both AG areas, PGa and PGp, were strongly deactivated in both tasks, with stronger deactivations in posterior area PGp. Compared with the more difficult MA-R task, the MA-A task showed greater responses in both AG areas, but this effect was driven by less deactivation in the MA-A task. AG deactivations showed prominent overlap with lateral parietal nodes of the default mode network, suggesting a nonspecific role in MA. In both tasks, greater bilateral AG deactivation was associated with poorer performance. Our findings suggest a close link between IPC structure and function and they provide new evidence for behaviorally salient functional heterogeneity within the IPC during mathematical cognition.

Abstract

EEG data acquired in an MRI scanner are heavily contaminated by gradient artifacts that can significantly compromise signal quality. We developed two new methods based on independent component analysis (ICA) for reducing gradient artifacts from spiral in-out and echo-planar pulse sequences at 3 T, and compared our algorithms with four other commonly used methods: average artifact subtraction (Allen, P., Josephs, O., Turner, R., 2000. A method for removing imaging artifact from continuous EEG recorded during functional MRI. NeuroImage 12, 230-239.), principal component analysis (Niazy, R., Beckmann, C., Iannetti, G., Brady, J., Smith, S., 2005. Removal of FMRI environment artifacts from EEG data using optimal basis sets. NeuroImage 28, 720-737.), Taylor series ( Wan, X., Iwata, K., Riera, J., Kitamura, M., Kawashima, R., 2006. Artifact reduction for simultaneous EEG/fMRI recording: adaptive FIR reduction of imaging artifacts. Clin. Neurophysiol. 117, 681-692.) and a conventional temporal ICA algorithm. Models of gradient artifacts were derived from simulations as well as a water phantom and performance of each method was evaluated on datasets constructed using visual event-related potentials (ERPs) as well as resting EEG. Our new methods recovered ERPs and resting EEG below the beta band (<12.5 Hz) with high signal-to-noise ratio (SNR>4). Our algorithms outperformed all of these methods on resting EEG in the theta and alpha bands (SNR>4); however, for all methods, signal recovery was modest (SNR approximately 1) in the beta band and poor (SNR<0.3) in the gamma band and above. We found that the conventional ICA algorithm performed poorly with uniformly low SNR (<0.1). Taken together, our new ICA-based methods offer a more robust technique for gradient artifact reduction when scanning at 3 T using spiral in-out and echo-planar pulse sequences. We provide new insights into the strengths and weaknesses of each method using a unified subspace framework.

Abstract

Poor mathematical abilities adversely affect academic and career opportunities. The neuroanatomical basis of developmental dyscalculia (DD), a specific learning deficit with prevalence rates exceeding 5%, is poorly understood. We used structural MRI and diffusion tensor imaging (DTI) to examine macro- and micro-structural impairments in 7- to 9-year-old children with DD, compared to a group of typically developing (TD) children matched on age, gender, intelligence, reading abilities and working memory capacity. Voxel-based morphometry (VBM) revealed reduced grey matter (GM) bilaterally in superior parietal lobule, intra-parietal sulcus, fusiform gyrus, parahippocampal gyrus and right anterior temporal cortex in children with DD. VBM analysis also showed reduced white matter (WM) volume in right temporal-parietal cortex. DTI revealed reduced fractional anisotropy (FA) in this WM region, pointing to significant right hemisphere micro-structural impairments. Furthermore, FA in this region was correlated with numerical operations but not verbal mathematical reasoning or word reading. Atlas-based tract mapping identified the inferior longitudinal fasciculus, inferior fronto-occipital fasciculus and caudal forceps major as key pathways impaired in DD. DTI tractography suggests that long-range WM projection fibers linking the right fusiform gyrus with temporal-parietal WM are a specific source of vulnerability in DD. Network and classification analysis suggest that DD in children may be characterized by multiple dysfunctional circuits arising from a core WM deficit. Our findings link GM and WM abnormalities in children with DD and they point to macro- and micro-structural abnormalities in right hemisphere temporal-parietal WM, and pathways associated with it, as key neuroanatomical correlates of DD.

Abstract

Despite ongoing debate about the nature of gender differences in mathematics achievement, little is known about gender similarities and differences in mathematical cognition at the neural level. We used fMRI to compare brain responses in 25 females and 24 males during a mental arithmetic task involving 3-operand addition and subtraction. We also used voxel-based morphometry (VBM) to examine gender differences in brain structure. Although females and males did not differ in accuracy or response times (effect size d<0.3), significant gender differences in functional brain activation were observed in the right dorsal and ventral visuospatial information processing streams (d>1.1). Males showed greater dorsal stream activation in the right intra-parietal sulcus areas important for numerical cognition, and angular gyrus regions of the default mode network that are typically deactivated during complex cognitive tasks, as well as greater ventral stream activation in the right lingual and parahippocampal gyri. VBM revealed an opposite pattern of gender differences-compared to males, females had greater regional density and greater regional volume in dorsal and ventral stream regions where males showed greater fMRI activation. There were no brain areas where females showed greater functional activation than males, and no brain areas where males showed greater structural density or volume than females. Our findings provide evidence for gender differences in the functional and structural organization of the right hemisphere brain areas involved in mathematical cognition. Together with the lack of behavioral differences, our results point to more efficient use of neural processing resources in females.

Abstract

The anterior insula has been hypothesized to provide a link between attention-related problem solving and salience systems during the coordination and evaluation of task performance. Here, we test the hypothesis that the anterior insula/medial frontal operculum (aI/fO) provides linkage across systems supporting task demands and attention systems by examining the patterns of functional connectivity during word recognition and spatial attention functional imaging tasks. A shared set of frontal regions (right aI/fO, right dorsolateral prefrontal cortex, bilateral anterior cingulate) were engaged, regardless of perceptual domain (auditory or visual) or mode of response (word production or button press). We present novel evidence that: (1) the right aI/fO is functionally connected with other frontal regions implicated in executive function and not just brain regions responsive to stimulus salience; and (2) that the aI/fO, but not the ACC, exhibits significantly correlated activity with other brain regions specifically engaged by tasks with varying perceptual and behavioral demands. These results support the hypothesis that the right aI/fO aids in the coordination and evaluation of task performance across behavioral tasks with varying perceptual and response demands.

Abstract

Convergent data from various scientific approaches strongly implicate cerebellar systems in nonmotor functions. The functional anatomy of these systems has been pieced together from disparate sources, such as animal studies, lesion studies in humans, and structural and functional imaging studies in humans. To better define this distinct functional anatomy, in the current study we delineate the role of the cerebellum in several nonmotor systems simultaneously and in the same subjects using resting state functional connectivity MRI. Independent component analysis was applied to resting state data from two independent datasets to identify common cerebellar contributions to several previously identified intrinsic connectivity networks (ICNs) involved in executive control, episodic memory/self-reflection, salience detection, and sensorimotor function. We found distinct cerebellar contributions to each of these ICNs. The neocerebellum participates in (1) the right and left executive control networks (especially crus I and II), (2) the salience network (lobule VI), and (3) the default-mode network (lobule IX). Little to no overlap was detected between these cerebellar regions and the sensorimotor cerebellum (lobules V-VI). Clusters were also located in pontine and dentate nuclei, prominent points of convergence for cerebellar input and output, respectively. The results suggest that the most phylogenetically recent part of the cerebellum, particularly crus I and II, make contributions to parallel cortico-cerebellar loops involved in executive control, salience detection, and episodic memory/self-reflection. The largest portions of the neocerebellum take part in the executive control network implicated in higher cognitive functions such as working memory.

Abstract

The common factor that underlies several types of functional brain imaging is the electric current of masses of dendrites. The prodigious demands for the energy that is required to drive the dendritic currents are met by hemodynamic and metabolic responses that are visualized with fMRI and PET techniques. The high current densities in parallel dendritic shafts and the broad distributions of the loop currents outside the dendrites generate both the scalp EEG and the magnetic fields seen in the MEG. The measurements of image intensities and potential fields provide state variables for modeling. The relationships between the intensities of current density and the electric, magnetic, and hemodynamic state variables are complex and far from proportionate. The state variables are complementary, because the information they convey comes from differing albeit overlapping neural populations, so that efforts to cross-validate localization of neural activity relating to specified cognitive behaviors have not always been successful. We propose an alternative way to use the three methods in combination through studies of hemisphere-wide, high-resolution spatiotemporal patterns of neural activity recorded non-invasively and analyzed with multivariate statistics. Success in this proposed endeavor requires specification of what patterns to look for. At the present level of understanding, an appropriate pattern is any significant departure from random noise in the spectral, temporal and spatial domains that can be scaled into the coarse-graining of time by fMRI/BOLD and the coarse-graining of space by EEG and MEG. Here the requisite patterns are predicted to be large-scale spatial amplitude modulation (AM) of synchronized neuronal signals in the beta and gamma ranges that are coordinated but not correlated with fMRI intensities.

Abstract

Volumetric imaging research has shown abnormal brain morphology in posttraumatic stress disorder (PTSD) when compared with control subjects. We present results on a study of brain morphology in the prefrontal cortex (PFC) and midline structures, via indices of gray matter volume and density, in pediatric PTSD. We hypothesized that both methods would demonstrate aberrant morphology in the PFC. Further, we hypothesized aberrant brainstem anatomy and reduced corpus callosum volume in children with PTSD. Twenty-four children (aged 7-14) with history of interpersonal trauma and 24 age- and gender-matched controls underwent structural magnetic resonance imaging (sMRI). Images of the PFC and midline brain structures were first analyzed using volumetric image analysis. The PFC data were then compared with whole brain voxel-based techniques using statistical parametric mapping (SPM). The PTSD group showed significantly increased gray matter volume in the right and left inferior and superior quadrants of the PFC and smaller gray matter volume in the pons and posterior vermis areas by volumetric image analysis. The voxel-by-voxel group comparisons demonstrated increased gray matter density mostly localized to ventral PFC as compared with the control group. Abnormal frontal lobe morphology, as revealed by separate-complementary image analysis methods, and reduced pons and posterior vermis areas are associated with pediatric PTSD. Voxel-based morphometry may help to corroborate and further localize data obtained by volume of interest methods in PTSD.

A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networksPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICASridharan, D., Levitin, D. J., Menon, V.2008; 105 (34): 12569-12574

Abstract

Cognitively demanding tasks that evoke activation in the brain's central-executive network (CEN) have been consistently shown to evoke decreased activation (deactivation) in the default-mode network (DMN). The neural mechanisms underlying this switch between activation and deactivation of large-scale brain networks remain completely unknown. Here, we use functional magnetic resonance imaging (fMRI) to investigate the mechanisms underlying switching of brain networks in three different experiments. We first examined this switching process in an auditory event segmentation task. We observed significant activation of the CEN and deactivation of the DMN, along with activation of a third network comprising the right fronto-insular cortex (rFIC) and anterior cingulate cortex (ACC), when participants perceived salient auditory event boundaries. Using chronometric techniques and Granger causality analysis, we show that the rFIC-ACC network, and the rFIC, in particular, plays a critical and causal role in switching between the CEN and the DMN. We replicated this causal connectivity pattern in two additional experiments: (i) a visual attention "oddball" task and (ii) a task-free resting state. These results indicate that the rFIC is likely to play a major role in switching between distinct brain networks across task paradigms and stimulus modalities. Our findings have important implications for a unified view of network mechanisms underlying both exogenous and endogenous cognitive control.

Abstract

The default-mode network (DMN) is a set of specific brain regions whose activity, predominant in the resting-state, is attenuated during cognitively demanding, externally-cued tasks. The cognitive correlates of this network have proven difficult to interrogate, but one hypothesis is that regions in the network process episodic memories and semantic knowledge integral to internally-generated mental activity. Here, we compare default-mode functional connectivity in the same group of subjects during rest and conscious sedation with midazolam, a state characterized by anterograde amnesia and a reduced level of consciousness. Although the DMN showed functional connectivity during both rest and conscious sedation, a direct comparison found that there was significantly reduced functional connectivity in the posterior cingulate cortex during conscious sedation. These results confirm that low-frequency oscillations in the DMN persist and remain highly correlated even at reduced levels of consciousness. We hypothesize that focal reductions in DMN connectivity, as shown here in the posterior cingulate cortex, may represent a stable correlate of reduced consciousness.

Abstract

Recent anatomical and electrophysiological evidence in primates indicates the presence of direct connections between primary auditory and primary visual cortex that constitute cross-modal systems. We examined the intrinsic functional connectivity (fcMRI) of putative primary auditory cortex in 32 young adults during resting state scanning. We found that the medial Heschl's gyrus was strongly coupled, in particular, to visual cortex along the anterior banks of the calcarine fissure. This observation was confirmed using novel group-level, tensor-based independent components analysis. fcMRI analysis revealed that although overall coupling between the auditory and visual cortex was significantly reduced when subjects performed a visual perception task, coupling between the anterior calcarine cortex and auditory cortex was not disrupted. These results suggest that primary auditory cortex has a functionally distinct relationship with the anterior visual cortex, which is known to represent the peripheral visual field. Our study provides novel, fcMRI-based, support for a neural system involving low-level auditory and visual cortices.

Abstract

Functional brain networks detected in task-free ("resting-state") functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.

Abstract

Although children's use of a variety of strategies to solve arithmetic problems has been well documented, there is no agreed on standardized and validated method for assessing this mix. We examined the convergent validity of typically achieving (TA, N = 39) and low achieving (LA, N = 20) second and third grade children's strategy choices in simple addition using three different methods: child self-report, observer-report, and response time (RT). The high concordance between child and observer reports (Kappa = .948) in both groups suggests that the participants were aware of, and could accurately report, the strategies they used. The Receiver-Operator Characteristic (ROC) analysis showed that RT accurately differentiated between retrieval and counting (AUC = 82%). The specificity and sensitivity of the ROC profiles were significantly greater for the TA group than for LA group, even though the groups did not differ in the overall strategy mix. Our findings suggest that ROC analysis is more sensitive to group differences in the mechanisms governing strategy choice than observation or child report. Children's use of retrieval strategies as well as accuracy during both retrieval and counting trials were all related to the central executive, but not the phonological and visuospatial sketchpad, component of working memory. We discuss the implication of these findings for early mathematical learning.

Abstract

Youth who experience interpersonal trauma and have posttraumatic stress symptoms (PTSS) can exhibit difficulties in executive function and physiological hyperarousal. Response inhibition has been identified as a core component of executive function. In this study, we investigate the functional neuroanatomical correlates of response inhibition in youth with PTSS. Thirty right-handed medication-naïve youth between the ages of 10 and 16 years underwent a 3-Tesla Functional Magnetic Resonance Imaging scan during a response-inhibition (Go/No-Go) task. Youth with PTSS (n = 16) were age and gender matched to a control group of healthy youth (n = 14). Between-groups analyses were conducted to identify brain regions of greater activation in the No/Go-Go contrasts. PTSS and control youth performed the task with similar accuracy and response times. Control subjects had greater middle frontal cortex activation when compared with PTSS subjects. PTSS subjects had greater medial frontal activation when compared with control subjects. A sub-group of youth with PTSS and a history of self-injurious behaviors demonstrated increased insula and orbitofrontal activation when compared with those PTSS youth with no self-injurious behaviors. Insula activation correlated positively with PTSS severity. Diminished middle frontal activity and enhanced medial frontal activity during response-inhibition tasks may represent underlying neurofunctional markers of PTSS.

Abstract

Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network--the default-mode network--that includes medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy controls.Twenty-eight subjects with major depression and 20 healthy controls underwent 5-min fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were compared. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on functional connectivity.Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were significantly greater in the depressed subjects. Within the depressed group, the length of the current depressive episode correlated positively with functional connectivity in the subgenual cingulate.This is the first study to explore default-mode functional connectivity in major depression. The findings provide cross-modality confirmation of PET studies demonstrating increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy in individual subjects.

Abstract

The real world presents our sensory systems with a continuous stream of undifferentiated information. Segmentation of this stream at event boundaries is necessary for object identification and feature extraction. Here, we investigate the neural dynamics of event segmentation in entire musical symphonies under natural listening conditions. We isolated time-dependent sequences of brain responses in a 10 s window surrounding transitions between movements of symphonic works. A strikingly right-lateralized network of brain regions showed peak response during the movement transitions when, paradoxically, there was no physical stimulus. Model-dependent and model-free analysis techniques provided converging evidence for activity in two distinct functional networks at the movement transition: a ventral fronto-temporal network associated with detecting salient events, followed in time by a dorsal fronto-parietal network associated with maintaining attention and updating working memory. Our study provides direct experimental evidence for dissociable and causally linked ventral and dorsal networks during event segmentation of ecologically valid auditory stimuli.

Abstract

Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.

Abstract

Research on the neural basis of working memory (WM) has generally focused on neocortical regions; comparatively little is known about the role of subcortical structures. There is growing evidence that the basal ganglia are involved in WM, but their contribution to different component processes of WM is poorly understood. We examined the temporal dynamics of basal ganglia response and connectivity during the encoding, maintenance and response phases of a Sternberg WM task. During the encoding and maintenance phases, WM-load-dependent activation was observed in the left anterior caudate, anterior putamen and globus pallidus; activation in the right anterior caudate was observed only during the maintenance phase. During the response phase, the basal ganglia were equally active in both the high-load and low-load WM conditions. Caudate and putamen activations were primarily localized to the (rostral) associative parts of the basal ganglia, consistent with the putative role of these regions in cognitive processing. Effective connectivity analyses revealed increased WM-load-dependent interaction of the left anterior caudate with the left posterior parietal cortex during all three phases of the task; with the visual association cortex, including the fusiform gyrus and inferior temporal gyrus, only during the encoding phase; with the ventrolateral prefrontal cortex during the encoding and maintenance phases; with the pre-supplementary motor area during the maintenance and response phases; and with the dorsolateral prefrontal and anterior cingulate cortices only during the response phase. Taken together with known neuroanatomy of the basal ganglia, these results suggest that the anterior caudate helps to link signals in distinct functional networks during different phases of the WM task. Our study offers new insight into the integrative and adaptive role of the basal ganglia in higher cognitive function.

Abstract

Turner syndrome (TS) is a neurogenetic disorder characterized by the absence of one X chromosome in a phenotypic female. Individuals with TS are at risk for impairments in mathematics. We investigated the neural mechanisms underlying arithmetic processing in TS. Fifteen subjects with TS and 15 age-matched typically developing controls were scanned using functional MRI while they performed easy (two-operand) and difficult (three-operand) versions of an arithmetic processing task. Both groups activated fronto-parietal regions involved in arithmetic processing during the math tasks. Compared with controls, the TS group recruited additional neural resources in frontal and parietal regions during the easier, two-operand math task. During the more difficult three-operand task, individuals with TS demonstrated significantly less activation in frontal, parietal and subcortical regions than controls. However, the TS group's performance on both math tasks was comparable to controls. Individuals with TS demonstrate activation differences in fronto-parietal areas during arithmetic tasks compared with controls. They must recruit additional brain regions during a relatively easy task and demonstrate a potentially inefficient response to increased task difficulty compared with controls.

Abstract

Directed attention, the ability to allocate and direct attention toward a salient stimulus, is impaired in attention deficit hyperactivity disorder (ADHD). This construct is often assessed with target detection or oddball tasks, and individuals with ADHD perform poorly on such tasks. However, to date, the specific brain structures or neural mechanisms underlying target detection dysfunction in individuals with ADHD have not been identified. The authors' goal was to investigate neural correlates of target detection dysfunction in ADHD using event-related fMRI.Behavioral and brain activation data were collected while subjects performed a visual oddball task. Participants included 14 right-handed male adolescents with ADHD (combined type) and 12 typically developing age- and handedness-matched male comparison subjects.Individuals with ADHD made significantly more errors of commission than comparison subjects. Further, relative to comparison subjects, individuals with ADHD showed significantly less activation in the bilateral parietal lobes (including the superior parietal gyrus and supramarginal and angular gyri of the inferior parietal lobe), right precuneus, and thalamus.Adolescents with ADHD demonstrated significant impairments in their ability to direct and allocate attentional resources. These difficulties were associated with significant aberrations in the parietal attentional system, which is known to play a significant role in attention shifting and detecting specific or salient targets. Thus, dysfunction in the parietal attentional system may play a significant role in the behavioral phenotype of ADHD.

Abstract

Attentional control provides top-down influences that allow task-relevant stimuli and responses to be processed preferentially. The anterior cingulate cortex (ACC) plays an important role in attentional control, but the spatiotemporal dynamics underlying this process is poorly understood. We examined the activation and connectivity of the ACC using functional magnetic resonance imaging (fMRI) along with fMRI-constrained dipole modeling of event-related potentials (ERPs) obtained from subjects who performed auditory and visual oddball attention tasks. Although attention-related responses in the ACC were similar in the two modalities, effective connectivity analyses showed modality-specific effects with increased ACC influences on the Heschl and superior temporal gyri during auditory task and on the striate cortex during visual task. Dipole modeling of ERPs based on source locations determined from fMRI activations showed that the ACC was the major generator of N2b-P3a attention-related components in both modalities, and that primary sensory regions generated a small mismatch signal about 50 msec prior to feedback from the ACC and a large signal 60 msec after feedback from the ACC. Taken together, these results provide converging neuroimaging and electrophysiological evidence for top-down attentional modulation of sensory processing by the ACC. Our findings suggest a model of attentional control based on dynamic bottom-up and top-down interactions between the ACC and primary sensory regions.

Abstract

Maturation of brain white matter pathways is an important factor in cognitive, behavioral, emotional and motor development during childhood and adolescence. In this study, we investigate white matter maturation as reflected by changes in anisotropy and white matter density with age. Thirty-four children and adolescents aged 6-19 years received diffusion-weighted magnetic resonance imaging scans. Among these, 30 children and adolescents also received high-resolution T1-weighed anatomical scans. A linear regression model was used to correlate fractional anisotropy (FA) values with age on a voxel-by-voxel basis. Within the regions that showed significant FA changes with age, a post hoc analysis was performed to investigate white matter density changes. With increasing age, FA values increased in prefrontal regions, in the internal capsule as well as in basal ganglia and thalamic pathways, the ventral visual pathways, and the corpus callosum. The posterior limb of the internal capsule, intrathalamic connections, and the corpus callosum showed the most significant overlaps between white matter density and FA changes with age. This study demonstrates that during childhood and adolescence, white matter anisotropy changes in brain regions that are important for attention, motor skills, cognitive ability, and memory. This typical developmental trajectory may be altered in individuals with disorders of development, cognition and behavior.

Abstract

Velocardiofacial syndrome (VCFS) is a congenital anomaly that causes somatic as well as cognitive and psychiatric impairments. Previous studies have found specific deficits in arithmetic abilities in subjects with VCFS. In this study, we investigated whether abnormalities in white matter pathways are correlated with reduced arithmetic ability. Nineteen individuals with VCFS aged 7-19 years received diffusion-weighted magnetic resonance imaging (MRI) scans. A linear regression model was used to correlate fractional anisotropy (FA) values with scores of the arithmetic subscale on the WISC/WAIS on a voxel-by-voxel basis, after covarying for any IQ- and age-related effects. There was a statistically significant positive correlation between the arithmetic score on the WISC/WAIS and FA values in white matter tracts adjacent to the left supramarginal and angular gyri, as well as along the left intraparietal sulcus. Inferior parietal lobe white matter structural aberrations may contribute to reduced arithmetic ability in VCFS.

Sex differences in brain activation elicited by humorPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAAzim, E., Mobbs, D., Jo, B., Menon, V., Reiss, A. L.2005; 102 (45): 16496-16501

Abstract

With recent investigation beginning to reveal the cortical and subcortical neuroanatomical correlates of humor appreciation, the present event-related functional MRI (fMRI) study was designed to elucidate sex-specific recruitment of these humor related networks. Twenty healthy subjects (10 females) underwent fMRI scanning while subjectively rating 70 verbal and nonverbal achromatic cartoons as funny or unfunny. Data were analyzed by comparing blood oxygenation-level-dependent signal activation during funny and unfunny stimuli. Males and females share an extensive humor-response strategy as indicated by recruitment of similar brain regions: both activate the temporal-occipital junction and temporal pole, structures implicated in semantic knowledge and juxtaposition, and the inferior frontal gyrus, likely to be involved in language processing. Females, however, activate the left prefrontal cortex more than males, suggesting a greater degree of executive processing and language-based decoding. Females also exhibit greater activation of mesolimbic regions, including the nucleus accumbens, implying greater reward network response and possibly less reward expectation. These results indicate sex-specific differences in neural response to humor with implications for sex-based disparities in the integration of cognition and emotion.

Personality predicts activity in reward and emotional regions associated with humorPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAMobbs, D., Hagan, C. C., Azim, E., Menon, V., Reiss, A. L.2005; 102 (45): 16502-16506

Abstract

Previous research and theory suggest that two stable personality dimensions, extroversion and neuroticism, differentially influence emotional reactivity to a variety of pleasurable phenomena. Here, we use event-related functional MRI to address the putative neural and behavioral associations between humor appreciation and the personality dimensions of introversion-extroversion and emotional stability-neuroticism. Our analysis showed extroversion to positively correlate with humor-driven blood oxygenation level-dependent signal in discrete regions of the right orbital frontal cortex, ventrolateral prefrontal cortex, and bilateral temporal cortices. Introversion correlated with increased activation in several regions, most prominently the bilateral amygdala. Although neuroticism did not positively correlate with any whole-brain activation, emotional stability (i.e., the inverse of neuroticism) correlated with increased activation in the mesocortical-mesolimbic reward circuitry encompassing the right orbital frontal cortex, caudate, and nucleus accumbens. Our findings tie together existing neurobiological studies of humor appreciation and are compatible with the notion that personality style plays a fundamental role in the neurobiological systems subserving humor appreciation.

Abstract

Arithmetic reasoning is arguably one of the most important cognitive skills a child must master. Here we examine neurodevelopmental changes in mental arithmetic. Subjects (ages 8-19 years) viewed arithmetic equations and were asked to judge whether the results were correct or incorrect. During two-operand addition or subtraction trials, for which accuracy was comparable across age, older subjects showed greater activation in the left parietal cortex, along the supramarginal gyrus and adjoining anterior intra-parietal sulcus as well as the left lateral occipital temporal cortex. These age-related changes were not associated with alterations in gray matter density, and provide novel evidence for increased functional maturation with age. By contrast, younger subjects showed greater activation in the prefrontal cortex, including the dorsolateral and ventrolateral prefrontal cortex and the anterior cingulate cortex, suggesting that they require comparatively more working memory and attentional resources to achieve similar levels of mental arithmetic performance. Younger subjects also showed greater activation of the hippocampus and dorsal basal ganglia, reflecting the greater demands placed on both declarative and procedural memory systems. Our findings provide evidence for a process of increased functional specialization of the left inferior parietal cortex in mental arithmetic, a process that is accompanied by decreased dependence on memory and attentional resources with development.

The rewards of music listening: Response and physiological connectivity of the mesolimbic systemNEUROIMAGEMenon, V., Levitin, D. J.2005; 28 (1): 175-184

Abstract

Although the neural underpinnings of music cognition have been widely studied in the last 5 years, relatively little is known about the neuroscience underlying emotional reactions that music induces in listeners. Many people spend a significant amount of time listening to music, and its emotional power is assumed but not well understood. Here, we use functional and effective connectivity analyses to show for the first time that listening to music strongly modulates activity in a network of mesolimbic structures involved in reward processing including the nucleus accumbens (NAc) and the ventral tegmental area (VTA), as well as the hypothalamus and insula, which are thought to be involved in regulating autonomic and physiological responses to rewarding and emotional stimuli. Responses in the NAc and the VTA were strongly correlated pointing to an association between dopamine release and NAc response to music. Responses in the NAc and the hypothalamus were also strongly correlated across subjects, suggesting a mechanism by which listening to pleasant music evokes physiological reactions. Effective connectivity confirmed these findings, and showed significant VTA-mediated interaction of the NAc with the hypothalamus, insula, and orbitofrontal cortex. The enhanced functional and effective connectivity between brain regions mediating reward, autonomic, and cognitive processing provides insight into understanding why listening to music is one of the most rewarding and pleasurable human experiences.

Abstract

The medial temporal lobe (MTL) plays an important role in memory encoding. The development and maturation of MTL and other brain regions involved in memory encoding are, however, poorly understood. We used functional magnetic resonance imaging to examine activation and effective connectivity of the MTL in children and adolescents during encoding of outdoor visual scenes. Here, we show that MTL response decreases with age whereas its connectivity with the left dorsolateral prefrontal cortex (PFC) increases with age. Our findings provide evidence for dissociable maturation of local and distributed memory encoding processes involving the MTL and furthermore suggest that increased functional interactions between the MTL and the PFC may underlie the development of more effective memory encoding strategies.

Abstract

Electroencephalogram (EEG) data acquired in the MRI scanner contains significant artifacts, one of the most prominent of which is ballistocardiogram (BCG) artifact. BCG artifacts are generated by movement of EEG electrodes inside the magnetic field due to pulsatile changes in blood flow tied to the cardiac cycle. Independent Component Analysis (ICA) is a statistical algorithm that is useful for removing artifacts that are linearly and independently mixed with signals of interest. Here, we demonstrate and validate the usefulness of ICA in removing BCG artifacts from EEG data acquired in the MRI scanner. In accordance with our hypothesis that BCG artifacts are physiologically independent from EEG, it was found that ICA consistently resulted in five to six independent components representing the BCG artifact. Following removal of these components, a significant reduction in spectral power at frequencies associated with the BCG artifact was observed. We also show that our ICA-based procedures perform significantly better than noise-cancellation methods that rely on estimation and subtraction of averaged artifact waveforms from the recorded EEG. Additionally, the proposed ICA-based method has the advantage that it is useful in situations where ECG reference signals are corrupted or not available.

Abstract

Recent models of hippocampal function have emphasized its role in processing sequences of events. In this study, we used an oddball task to investigate hippocampal responses to the detection of deviant "target" stimuli that were embedded in a sequence of repetitive "standard" stimuli. Evidence from intracranial event-related potential studies has suggested a critical role for the hippocampus in oddball tasks. However, functional neuroimaging experiments have failed to detect activation in the hippocampus in response to deviant stimuli. Our study aimed to resolve this discrepancy by using a novel functional magnetic resonance imaging (fMRI) technique that drastically improves signal detection in the hippocampus. Significant hippocampal activation was observed during both auditory and visual oddball tasks. Although there was no difference in the overall level of hippocampal activation in the two modalities, significant modality differences in the profile of activation along the long axis of the hippocampus were observed. In both left and right hippocampi, an anterior-to-posterior gradient in the activation (anterior to posterior) was observed during the auditory oddball task, whereas a posterior-to-anterior gradient (posterior to anterior) was observed during the visual oddball task. These results indicate that the hippocampus is involved in the detection of deviant stimuli regardless of stimulus modality, and that there are prominent modality differences along the long axis of the hippocampus. The implications of our findings for understanding hippocampal involvement in processing sequences of events are discussed.

Abstract

Deactivation refers to increased neural activity during low-demand tasks or rest compared with high-demand tasks. Several groups have reported that a particular set of brain regions, including the posterior cingulate cortex and the medial prefrontal cortex, among others, is consistently deactivated. Taken together, these typically deactivated brain regions appear to constitute a default-mode network of brain activity that predominates in the absence of a demanding external task. Examining a passive, block-design sensory task with a standard deactivation analysis (rest epochs vs. stimulus epochs), we demonstrate that the default-mode network is undetectable in one run and only partially detectable in a second run. Using independent component analysis, however, we were able to detect the full default-mode network in both runs and to demonstrate that, in the majority of subjects, it persisted across both rest and stimulus epochs, uncoupled from the task waveform, and so mostly undetectable as deactivation. We also replicate an earlier finding that the default-mode network includes the hippocampus suggesting that episodic memory is incorporated in default-mode cognitive processing. Furthermore, we show that the more a subject's default-mode activity was correlated with the rest epochs (and "deactivated" during stimulus epochs), the greater that subject's activation to the visual and auditory stimuli. We conclude that activity in the default-mode network may persist through both experimental and rest epochs if the experiment is not sufficiently challenging. Time-series analysis of default-mode activity provides a measure of the degree to which a task engages a subject and whether it is sufficient to interrupt the processes--presumably cognitive, internally generated, and involving episodic memory--mediated by the default-mode network.

Abstract

Response inhibition deficits are characteristic of individuals with attention-deficit/hyperactivity disorder (ADHD). Previous functional magnetic resonance imaging (fMRI) studies investigating the neural correlates of this dysfunction have used block designs, making it difficult to disentangle activation differences specifically related to response inhibition from activation differences related to subprocesses involved in task performance. The current study was designed to further enhance our understanding of this critical function in individuals with ADHD using event-related fMRI.Ten adolescent boys diagnosed with ADHD, combined type, and 12 typically developing controls completed a Go/NoGo task modified to control for novelty processing.The ADHD group made significantly more errors of omission and more errors of commission than the control group. Further, compared with controls, individuals with ADHD showed marked abnormalities in brain activation during response inhibition, including hypoactivation of the anterior/mid-cingulate cortex extending to the supplementary motor area and hyperactivation of the left temporal gyrus.The authors suggest that underactivation in frontal regions reflects core deficits in response/task-switching abilities for the ADHD group.

Abstract

The neurobiological features of pediatric bipolar disorder (BD) are largely unknown. Children and adolescents with BD may be important to study with functional neuroimaging techniques because of their unique status of early-onset BD and high familial loading for the disorder. Neuroimaging studies of adults with BD have implicated the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) in the development of this disorder.To study children and adolescents with BD via functional magnetic resonance imaging using cognitive and affective tasks and to examine possible abnormalities in the DLPFC and ACC, as well as selected subcortical areas, in pediatric familial BD.We evaluated 12 male subjects aged 9 to 18 years with BD who had at least 1 parent with BD as well as 10 age- and IQ-matched healthy male controls. Stimulants were discontinued for at least 24 hours; other medications were continued. Subjects underwent functional magnetic resonance imaging at 3 T while performing a 2-back visuospatial working memory task and an affective task involving the visualization of positively, neutrally, or negatively valenced pictures.An academic referral setting, drawing from the Bay Area of San Francisco, Calif.Compared with controls, for the visuospatial working memory task, subjects with BD had greater activation in several areas including the bilateral ACC, left putamen, left thalamus, left DLPFC, and right inferior frontal gyrus. Controls had greater activation in the cerebellar vermis. In viewing negatively valenced pictures, subjects with BD had greater activation in the bilateral DLPFC, inferior frontal gyrus, and right insula. Controls had greater activation in the right posterior cingulate gyrus. For positively valenced pictures, subjects with BD had greater activation in the bilateral caudate and thalamus, left middle/superior frontal gyrus, and left ACC, whereas controls had no areas of greater activation.Children and adolescents with BD may have underlying abnormalities in the regulation of prefrontal-subcortical circuits. Further functional magnetic resonance imaging studies of attention and mood with greater sample sizes are needed.

Abstract

Fragile X syndrome (FraX), the most common heritable cause of developmental disability, is associated with IQ, memory, and visuospatial processing deficits. The fragile X gene (FMR1) is prominently transcribed in two regions critical to memory encoding and attention: the hippocampus and the basal forebrain. To probe functional MRI activation abnormalities associated with the disorder, girls with FraX and age-matched, normally-developing girls were scanned during a test of visual memory encoding. While there were considerable similarities in activation patterns between the two groups, the girls with FraX showed significantly less activation in the hippocampus and the basal forebrain. This is the first study, to our knowledge, demonstrating functional deficits in FraX subjects in brain regions known to have the highest FMR1 transcription.

Abstract

To investigate the discrete neural systems that underlie relatively preserved face processing skills in Williams syndrome (WS).The authors compared face and eye-gaze direction processing abilities in 11 clinically and genetically diagnosed WS subjects with 11 healthy age- and sex-matched controls, using functional MRI (fMRI).Compared to controls, WS subjects showed a strong trend toward being less accurate in determining the direction of gaze and had significantly longer response latencies. Significant increases in activation were observed in the right fusiform gyrus (FuG) and several frontal and temporal regions for the WS group. By comparison, controls showed activation in the bilateral FuG, occipital, and temporal lobes. Between-group analysis showed WS subjects to have more extensive activation in the right inferior, superior, and medial frontal gyri, anterior cingulate, and several subcortical regions encompassing the anterior thalamus and caudate. Conversely, controls had greater activation in the primary and secondary visual cortices.The observed patterns of activation in WS subjects suggest a preservation of neural functioning within frontal and temporal regions, presumably resulting from task difficulty or compensatory mechanisms. Persons with WS may possess impairments in visual cortical regions, possibly disrupting global-coherence and visuospatial aspects of face and gaze processing.

Abstract

To determine whether expertise in the attribution of emotion from basic facial expressions in high-functioning individuals with autistic spectrum disorder (ASD) is supported by the amygdala, fusiform, and prefrontal regions of interest (ROI) and is comparable to that of typically developing individuals.Functional magnetic resonance imaging scans were acquired from 14 males with ASD and 10 matched adolescent controls while performing emotion match (EM) (perceptual), emotion label (EL) (linguistic), and control tasks. Accuracy, response time, and average activation were measured for each ROI.There was no significant difference in accuracy, response time, or ROI activation between groups performing the EL task. The ASD group was as accurate as the control group performing the EM task but had a significantly longer response time and lower average fusiform activation.Expertise in the attribution of emotion from basic facial expressions was task-dependent in the high-functioning ASD group. The hypothesis that the high-functioning ASD group would be less expert and would have reduced fusiform activation was supported in the perceptual task but not the linguistic task. The reduced fusiform activation in the perceptual task was not explained by reduced expertise; it is therefore concluded that reduced fusiform activation is associated with the diagnosis of ASD.

Abstract

Recent functional imaging studies have revealed coactivation in a distributed network of cortical regions that characterizes the resting state, or default mode, of the human brain. Among the brain regions implicated in this network, several, including the posterior cingulate cortex and inferior parietal lobes, have also shown decreased metabolism early in the course of Alzheimer's disease (AD). We reasoned that default-mode network activity might therefore be abnormal in AD. To test this hypothesis, we used independent component analysis to isolate the network in a group of 13 subjects with mild AD and in a group of 13 age-matched elderly controls as they performed a simple sensory-motor processing task. Three important findings are reported. Prominent coactivation of the hippocampus, detected in all groups, suggests that the default-mode network is closely involved with episodic memory processing. The AD group showed decreased resting-state activity in the posterior cingulate and hippocampus, suggesting that disrupted connectivity between these two regions accounts for the posterior cingulate hypometabolism commonly detected in positron emission tomography studies of early AD. Finally, a goodness-of-fit analysis applied at the individual subject level suggests that activity in the default-mode network may ultimately prove a sensitive and specific biomarker for incipient AD.

Frontostriatal deficits in fragile X syndrome: Relation to FMR1 gene expressionPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAMenon, V., Leroux, J., White, C. D., Reiss, A. L.2004; 101 (10): 3615-3620

Abstract

Fragile X syndrome (fraX) is the most common known cause of inherited developmental disability. fraX is associated with a CGG expansion in the FMR1 gene on the long arm of the X chromosome. Behavioral deficits, including problems with impulse control and distractibility, are common in fraX. We used functional brain imaging with a Go/NoGo task to examine the neural substrates of response inhibition in females with fraX (ages 10-22) and age- and gender-matched typically developing subjects. Although subjects with fraX had significantly lower IQ scores, as a group their performance on the Go/NoGo task was equivalent to that of the typically developing group. However, females with fraX showed abnormal activation patterns in several cortical and subcortical regions, with significantly reduced activation in the supplementary motor area, anterior cingulate and midcingulate cortex, basal ganglia, and hippocampus. An important finding of our study is that neural responses in the right ventrolateral prefrontal cortex (PFC) and the left and right striatum were correlated with the level of FMR1 gene expression. Our findings support the hypothesis that frontostriatal regions typically associated with response inhibition are dysfunctional in females with fraX. In addition to task-related activation deficits, reduced levels of "deactivation" were observed in the ventromedial PFC, and, furthermore, these reductions were correlated with the level of FMR1 gene expression. The ventromedial PFC is a key node in a "default mode" network that monitors mental and physiological states; we suggest that self-monitoring processes may be aberrant in fraX.

Abstract

Children with fragile X syndrome (fraX) are at risk for manifesting abnormalities in social function that overlap with features of autism and social anxiety disorder. In this study, we analyzed brain activation in response to face and gaze stimuli to better understand neural functioning associated with social perception in fraX.Eleven female subjects with fraX, aged 10 to 22 years, were compared with age-matched female control subjects. Photographs of forward-facing and angled faces, each having direct and averted gaze (4 types of stimuli), were presented in an event-related design during functional magnetic resonance imaging. Subjects were instructed to determine the direction of gaze for each photograph. Activation in brain regions known to respond to face and gaze stimuli, the fusiform gyrus (FG) and superior temporal sulcus (STS), were compared between groups to isolate neural abnormalities in the perception of directed social stimuli.The fraX subjects had decreased accuracy in determining the direction of gaze compared with controls. Region of interest analysis of the FG revealed a significant interaction between diagnostic group and face orientation. Specifically, control subjects had greater FG activation to forward than to angled faces, whereas fraX subjects had no difference in FG activation to forward and angled faces. Controls showed greater left STS activation to all stimuli compared with fraX subjects.Our results suggest that gaze aversion in fraX subjects is related to decreased specialization of the FG in the perception of face orientation. Decreased STS activation in fraX suggests aberrant processing of gaze. These data suggest that gaze aversion in fraX may be related to dysfunction of neural systems underlying both face and gaze processing.

Abstract

Turner syndrome (TS), a neurogenetic disorder characterized by the absence of one X chromosome in a phenotypic female, is frequently associated with visuospatial impairments. We investigated the neural mechanisms underlying deficits in spatial orientation processing in TS. Thirteen subjects with TS and 13 age-matched typically developing controls underwent neuropsychological assessments and were scanned using functional MRI while they performed easy and difficult versions of a judgment of line orientation (JLO) task. Controls and subjects with TS activated parietal-occipital regions involved in spatial orientation during the JLO task. However, activation was significantly less in the TS group. Control subjects responded to increased task difficulty by recruiting executive frontal areas whereas subjects with TS did not activate alternate brain regions to meet increased task demands. Subjects with TS demonstrate activation deficits in parietal-occipital and frontal areas during the JLO task. Activation, and possibly deactivation, deficits in these areas may be responsible for the visuospatial deficits observed in females with TS.

Abstract

Individuals with autism have severe difficulties in social communication and relationships. Prior studies have suggested that abnormal connections between brain regions important for social cognition may contribute to the social deficits seen in autism.In this study, we used diffusion tensor imaging to investigate white matter structure in seven male children and adolescents with autism and nine age-, gender-, and IQ-matched control subjects.Reduced fractional anisotropy (FA) values were observed in white matter adjacent to the ventromedial prefrontal cortices and in the anterior cingulate gyri as well as in the temporoparietal junctions. Additional clusters of reduced FA values were seen adjacent to the superior temporal sulcus bilaterally, in the temporal lobes approaching the amygdala bilaterally, in occipitotemporal tracts, and in the corpus callosum.Disruption of white matter tracts between regions implicated in social functioning may contribute to impaired social cognition in autism.

Abstract

The neural bases of verbal (nonspatial) working memory (VWM) have been primarily examined using visual stimuli. Few studies have investigated the neural bases of VWM using auditory stimuli, and fewer have explored modality differences in VWM. In this study, we used functional magnetic resonance imaging (fMRI) to examine similarities and differences between visual VWM (vis-VWM) and auditory VWM (aud-VWM) utilizing identical stimuli and a within-subjects design. Performance levels were similar in the two modalities and there was extensive overlap of activation bilaterally in the dorsolateral and ventrolateral prefrontal cortex (DLPFC and VLPFC), intraparietal sulcus, supramarginal gyrus and the basal ganglia. However, a direct statistical comparison revealed significant modality differences: the left posterior parietal cortex, primarily along the intraparietal sulcus, showed greater responses during vis-VWM whereas the left dorsolateral prefrontal cortex showed greater responses during aud-VWM. No such differences were observed in the right hemisphere. Other modality differences in VWM were also observed, but they were associated with relative decreases in activation. In particular, we detected bilateral suppression of the superior and middle temporal (auditory) cortex during vis-VWM, and of the occipital (visual) cortex during aud-VWM, thus suggesting that cross-modal inhibitory processes may help to provide preferential access to high-order heteromodal association areas. Taken together, our findings suggest that although similar prefrontal and parietal regions are involved in aud-VWM and vis-VWM, there are important modality differences in the way neural signals are generated, processed and routed during VWM.

Abstract

Humor plays an essential role in many facets of human life including psychological, social, and somatic functioning. Recently, neuroimaging has been applied to this critical human attribute, shedding light on the affective, cognitive, and motor networks involved in humor processing. To date, however, researchers have failed to demonstrate the subcortical correlates of the most fundamental feature of humor-reward. In an effort to elucidate the neurobiological substrate that subserves the reward components of humor, we undertook a high-field (3 Tesla) event-related functional MRI study. Here we demonstrate that humor modulates activity in several cortical regions, and we present new evidence that humor engages a network of subcortical regions including the nucleus accumbens, a key component of the mesolimbic dopaminergic reward system. Further, the degree of humor intensity was positively correlated with BOLD signal intensity in these regions. Together, these findings offer new insight into the neural basis of salutary aspects of humor.

Musical structure is processed in "language" areas of the brain: a possible role for Brodmann Area 47 in temporal coherenceMeeting of the Society-for-Music-Perception-and-CognitionLevitin, D. J., Menon, V.ACADEMIC PRESS INC ELSEVIER SCIENCE.2003: 2142–52

Abstract

The neuroanatomical correlates of musical structure were investigated using functional magnetic neuroimaging (fMRI) and a unique stimulus manipulation involving scrambled music. The experiment compared brain responses while participants listened to classical music and scrambled versions of that same music. Specifically, the scrambled versions disrupted musical structure while holding low-level musical attributes constant, including the psychoacoustic features of the music such as pitch, loudness, and timbre. Comparing music to its scrambled counterpart, we found focal activation in the pars orbitalis region (Brodmann Area 47) of the left inferior frontal cortex, a region that has been previously closely associated with the processing of linguistic structure in spoken and signed language, and its right hemisphere homologue. We speculate that this particular region of inferior frontal cortex may be more generally responsible for processing fine-structured stimuli that evolve over time, not merely those that are linguistic.

Abstract

Velocardiofacial syndrome, caused by a deletion on chromosome 22q11.2, is often accompanied by cognitive, behavioral, and psychiatric impairments. Specifically, velocardiofacial syndrome has been proposed as a disease model for a genetically mediated subtype of schizophrenia. Velocardiofacial syndrome is also known to affect brain structure. The most prominent structural findings in velocardiofacial syndrome are reduced white matter volumes. However, the structure of white matter and extent of specific regional involvement in this syndrome have never been investigated. The current study used diffusion tensor imaging to investigate white matter structure in children and young adults with velocardiofacial syndrome.Nineteen participants with velocardiofacial syndrome and 19 age- and gender-matched comparison subjects underwent diffusion-weighted magnetic resonance imaging scans. Whole brain voxel-by-voxel analyses were conducted to investigate white matter fractional anisotropy differences between the groups.Relative to the comparison group, the velocardiofacial syndrome group had reduced white matter anisotropy in the frontal, parietal, and temporal regions as well as in tracts connecting the frontal and temporal lobes.This study demonstrates that alterations of white matter tract structure occur in velocardiofacial syndrome. Reduced white matter anisotropy was observed in individuals with velocardiofacial syndrome in areas previously implicated in the neurocognitive phenotype of velocardiofacial syndrome. The finding of aberrant parietal white matter tracts as well as aberrant frontotemporal connectivity in velocardiofacial syndrome and in previous schizophrenia studies may be associated with increased vulnerability for development of psychotic symptoms.

Abstract

We used functional MRI with an event-related design to dissociate the brain activation in the fusiform gyrus (FG) and posterior superior temporal sulcus (STS) for multiple face and gaze orientations. The event-related design allowed for concurrent behavioral analysis, which revealed a significant effect of both head and gaze orientation on the speed of gaze processing, with the face and gaze forward condition showing the fastest reaction times. In conjunction with this behavioral finding, the FG responded with the greatest activation to face and gaze forward, perhaps reflecting the unambiguous social salience of congruent face and gaze directed toward the viewer. Random effects analysis showed greater activation in both the FG and posterior STS when the subjects viewed a direct face compared to an angled face, regardless of gaze direction. Additionally, the FG showed greater activation for forward gaze compared to angled gaze, but only when the face was forward. Together, these findings suggest that head orientation has a significant effect on gaze processing and these effects are manifest not only in the STS, but also the FG.

Abstract

As a step toward bridging the gap between human and animal studies of olfactory brain systems, we report results from an fMRI study of olfaction in squirrel monkeys. High-resolution fMRI images at 3 T with 1.25 x 1.25 x 1.2 mm(3) voxels were obtained covering the whole brain using an 8-cm-diameter birdcage coil and a gradient-echo spiral pulse sequence. Data were acquired from six sedated adult males using a standard block design. All fMRI data were spatially normalized to a common template and analyzed at the individual and group levels with statistical parametric and nonparametric methods. Robust odorant-induced activations were detected in several brain regions previously implicated in conscious human olfactory processing, including the orbitofrontal cortex, cerebellum, and piriform cortex. Consistent with human data, no stimulus intensity effects were observed in any of these regions. Average signal changes in these regions exceeded 0.6%, more than three times the expected signal change based on human fMRI studies of olfaction adjusting for differences in voxel size. These results demonstrate the feasibility of studying olfaction in sedated monkeys with imaging techniques commonly used at 3 T in humans and help promote direct comparisons between humans and nonhuman primates. Our findings, for example, provide novel support for the hypothesis that the cerebellum is involved in sensory acquisition. More broadly, this study suggests that olfactory processing in sedated monkeys and nonsedated humans shares similar neural substrates both within and beyond the primary olfactory system.

Abstract

Fragile X syndrome, the most common form of hereditary mental retardation, causes disruption in the development of dendrites and synapses, the targets for axonal growth in the central nervous system. This disruption could potentially affect the development, wiring, and targeting of axons. The current study utilized diffusion tensor imaging (DTI) to investigate whether white matter tract integrity and connectivity are altered in fragile X syndrome. Ten females with a diagnosis of fragile X syndrome and ten, age matched, female control subjects underwent diffusion weighted MRI scans. A whole brain analysis of fractional anisotropy (FA) values was performed using statistical parametric mapping (SPM). A follow-up, regions-of-interest analysis also was conducted. Relative to controls, females with fragile X exhibited lower FA values in white matter in fronto-striatal pathways, as well as in parietal sensory-motor tracts. This preliminary study suggests that regionally specific alterations of white matter integrity occur in females with fragile X. Aberrant white matter connectivity in these regions is consistent with the profile of cognitive and behavioral features of fragile X syndrome, and potentially provide additional insight into the detrimental effects of suboptimal levels of FMRP in the developing brain.

Abstract

Previous studies comparing fMRI data acquired at 1.5 T and higher field strengths have focused on examining signal increases in the visual and motor cortices. No information is, however, available on the relative gain, or the comparability of data, obtained at higher field strengths for other brain regions such as the prefrontal and other association cortices. In the present study, we investigated fMRI activation at 1.5 and 3 T during visual perception, visuospatial working memory, and affect-processing tasks. A 23% increase in striate and extrastriate activation volume was observed at 3 T compared with that for 1.5 T during the visual perception task. During the working memory task significant increases in activation volume were observed in frontal and parietal association cortices as well as subcortical structures, including the caudate, globus pallidus, putamen, and thalamus. Increases in working memory-related activation volume of 82, 73, 83, and 36% were observed in the left frontal, right frontal, left parietal, and right parietal lobes, respectively, for 3 T compared with 1.5 T. These increases were characterized by increased activation at 3 T in several prefrontal and parietal cortex regions that showed activation at 1.5 T. More importantly, at 3 T, activation was detected in several regions, such as the ventral aspects of the inferior frontal gyrus, orbitofrontal gyrus, and lingual gyrus, which did not show significant activation at 1.5 T. No difference in height or extent of activation was detected between the two scanners in the amygdala during affect processing. Signal dropout in the amygdala from susceptibility artifact was greater at 3 T, with a 12% dropout at 3 T compared with a 9% dropout at 1.5 T. The spatial smoothness of T2* images was greater at 3 T by less than 1 mm, suggesting that the greater extent of activation at 3 T beyond these spatial scales was not due primarily to increased intrinsic spatial correlations at 3 T. Rather, the increase in percentage of voxels activated reflects increased sensitivity for detection of brain activation at higher field strength. In summary, our findings suggest that functional imaging of prefrontal and other association cortices can benefit significantly from higher magnetic field strength.

Abstract

Turner syndrome (TuS) arises from the partial or complete absence of one X chromosome. Although neuropsychological studies report impaired attentional function and response inhibition in TuS, the neural correlates of these cognitive problems are unknown.Eleven female subjects with TuS and 11 individually matched normal control subjects were imaged using functional magnetic resonance imaging while performing a Go/NoGo task.Groups did not differ on accuracy or reaction time; however, the TuS group activated more in the bilateral superior and middle frontal gyri than control subjects. Control subjects did not activate more than the TuS group in any region.These findings suggest that female subjects with TuS compensate for executive dysfunction via recruitment of additional prefrontal cortex regions involved in inhibition, attention, and working memory, functions necessary for successful performance of Go/NoGo tasks. Elucidating brain function in TuS will advance our understanding of the influence of X-chromosome genes on neurodevelopment and brain function and contribute to planning future intervention strategies.

Functional connectivity in the resting brain: A network analysis of the default mode hypothesisPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAGreicius, M. D., Krasnow, B., Reiss, A. L., Menon, V.2003; 100 (1): 253-258

Abstract

Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.

Abstract

Investigators have recently begun to examine the differential role of subregions of the hippocampus in episodic memory. Two distinct models have gained prominence in the field. One model, outlined by Moser and Moser (Hippocampus 1998;8:608-619), based mainly on animal studies, has proposed that episodic memory is subserved by the posterior two-thirds of the hippocampus alone. A second model, derived by Lepage et al. (Hippocampus 1998;8:313-322) from their review of 52 PET studies, has suggested that the anterior hippocampus is activated by memory encoding while the posterior hippocampus is activated by memory retrieval. Functional magnetic resonance imaging (fMRI) studies have tended to show limited activation in the anteriormost regions of the hippocampus, providing support for the Moser and Moser model. A potential confounding factor in these fMRI studies, however, is that susceptibility artifact may differentially reduce signal in the anterior versus the posterior hippocampus. In the present study, we examined activation differences between hippocampal subregions during encoding and retrieval of words and interpreted our findings within the context of these two models. We also examined the extent to which susceptibility artifact affects the analysis and interpretation of hippocampal activation by demonstrating its differential effect on the anterior versus the posterior hippocampus. Both voxel-by-voxel and region-of-interest analyses were conducted, allowing us to quantify differences between the anterior and posterior aspects of the hippocampus. We detected significant hippocampal activation in both the encoding and retrieval conditions. Our data do not provide evidence for regional anatomic differences in activation between encoding and retrieval. The data do suggest that, even after accounting for susceptibility artifact, both encoding and retrieval of verbal stimuli activate the middle and posterior hippocampus more strongly than the anterior hippocampus. Finally, this study is the first to quantify the effects of susceptibility-induced signal loss on hippocampal activation and suggests that this artifact has significantly biased the interpretation of earlier fMRI studies.

Abstract

Williams syndrome (WS), a neurogenetic developmental disorder, is characterized by a rare fractionation of higher cortical functioning: selective preservation of certain complex faculties (language, music, face processing, and sociability) in contrast to marked and severe deficits in nearly every other cognitive domain (reasoning, spatial ability, motor coordination, arithmetic, problem solving). WS people are also known to suffer from hyperacusis and to experience heightened emotional reactions to music and certain classes of noise. We used functional magnetic resonance imaging to examine the neural basis of auditory processing of music and noise in WS patients and age-matched controls and found strikingly different patterns of neural organization between the groups. Those regions supporting music and noise processing in normal subjects were found not to be consistently activated in the WS participants (e.g., superior temporal and middle temporal gyri). Instead, the WS participants showed significantly reduced activation in the temporal lobes coupled with significantly greater activation in the right amygdala. In addition, WS participants (but not controls) showed a widely distributed network of activation in cortical and subcortical structures, including the brain stem, during music processing. Taken together with previous ERP and cytoarchitectonic studies, this first published report of WS using fMRI provides additional evidence of a different neurofunctional organization in WS people than normal people, which may help to explain their atypical reactions to sound. These results constitute an important first step in drawing out the links between genes, brain, cognition, and behavior in Williams syndrome.

Abstract

Timbre is a major structuring force in music and one of the most important and ecologically relevant features of auditory events. We used sound stimuli selected on the basis of previous psychophysiological studies to investigate the neural correlates of timbre perception. Our results indicate that both the left and right hemispheres are involved in timbre processing, challenging the conventional notion that the elementary attributes of musical perception are predominantly lateralized to the right hemisphere. Significant timbre-related brain activation was found in well-defined regions of posterior Heschl's gyrus and superior temporal sulcus, extending into the circular insular sulcus. Although the extent of activation was not significantly different between left and right hemispheres, temporal lobe activations were significantly posterior in the left, compared to the right, hemisphere, suggesting a functional asymmetry in their respective contributions to timbre processing. The implications of our findings for music processing in particular and auditory processing in general are discussed.

Abstract

Most theories of amygdalar function have underscored its role in fear. One broader theory suggests that neuronal activation of the amygdala in response to fear-related stimuli represents only a portion of its more widespread role in modulating an organism's vigilance level. To further explore this theory, the amygdalar response to happy, sad, angry, fearful, and neutral faces in 17 subjects was characterized using 3 T fMRI. Utilizing a random effects model and hypothesis-driven analytic strategy, it was observed that each of the four emotional faces was associated with reliable bilateral activation of the amygdala compared with neutral. These findings suggest a broader role for the amygdala in modulating the vigilance level during the perception of several negative and positive facial emotions.

Abstract

To investigate the developmental trajectory of response inhibition and, more specifically, whether there is a dissociation of function in the prefrontal cortex over the course of development of executive function and associated response inhibition abilities.Nineteen typically developing subjects, ranging in age from 8 to 20, performed a Go/NoGo task while behavioral and functional magnetic resonance imaging (fMRI) data were collected.All subjects performed the task with few errors of omission and commission. No relationship between accuracy and age emerged, but the ability to inhibit responses significantly improved with age. Analyses of fMRI data revealed a positive correlation between activation and age in the left inferior frontal gyrus/insula/orbitofrontal gyrus, and a negative correlation between activation and age in the left middle/superior frontal gyri.These data provide the first evidence of dissociable processes occurring in the prefrontal cortex during development of executive functions associated with response inhibition: (1) Younger subjects activate more extensively than older subjects in discrete regions of the prefrontal cortex, presumably due to increased demands and inefficient recruitment of brain regions subserving executive functions including working memory. (2) Older subjects show increasingly focal activation in specific regions thought to play a more critical role in response inhibition.

Neural basis of protracted developmental changes in visuo-spatial working memoryPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICAKwon, H., Reiss, A. L., Menon, V.2002; 99 (20): 13336-13341

Abstract

Developmental studies have shown that visuo-spatial working memory (VSWM) performance improves throughout childhood and adolescence into young adulthood. The neural basis of this protracted development is poorly understood. In this study, we used functional MRI (fMRI) to examine VSWM function in children, adolescents, and young adults, ages 7-22. Subjects performed a 2-back VSWM experiment that required dynamic storage and manipulation of spatial information. Accuracy and response latency on the VSWM task improved gradually, extending into young adulthood. Age-related increases in brain activation were observed in focal regions of the left and right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex (including Broca's area), left premotor cortex, and left and right posterior parietal cortex. Multiple regression analysis was used to examine the relative contributions of age, accuracy, and response latency on activation. Our analysis showed that age was the most significant predictor of activation in these brain regions. These findings provide strong evidence for a process of protracted functional maturation of bilateral fronto-parietal neural networks involved in VSWM development. At least two neural systems involved in VSWM mature together: (i) a right hemisphere visuo-spatial attentional system, and (ii) a left hemisphere phonological storage and rehearsal system. These observations suggest that visually and verbally mediated mnemonic processes, and their neural representations, develop concurrently during childhood and adolescence and into young adulthood.

Abstract

Arithmetic processing deficits in persons with fragile X Syndrome (fraX), the most common heritable cause of mental retardation, are well known. In this study, we characterize the neural underpinnings of these performance deficits using functional MRI. Given that a single gene defect (FMR1) is known to be responsible for this disorder, we also assess whether brain activation in arithmetic processing areas is related to amount of FMR1 protein expression (FMRP). Subjects included 16 females with fraX, and 16 female age-matched controls. Subjects viewed arithmetic equations with two (1 + 3 = 4) or three (2 + 3 - 1 = 5) operands, and were asked to judge whether the results were correct or not. Subjects with fraX showed significant impairment in behavioral performance on the 3-operand but not the 2-operand arithmetic equations. Significant brain activation was observed bilaterally in the prefrontal and parietal cortices for unaffected subjects, and bilateral prefrontal and left angular gyrus for subjects with fraX, for both trial types. Subjects with fraX exhibited less overall activation than did unaffected subjects in both types of trials; and, unlike the unaffected group, did not show increased extent of activation in association with greater task difficulty. During the 3-operand trials, activation in bilateral prefrontal and motor/premotor, and left supramarginal and angular gyri were positively correlated with FMRP, suggesting that decreased FMR1 protein expression underlies deficits in math performance in persons with fraX. More broadly, this investigation demonstrates a unique bridging of cognitive and molecular neuroscience and represents a useful approach for the study of brain development and function.

Abstract

The main aim of this study was to investigate the differential processing of correct and incorrect equations to gain further insight into the neural processes involved in arithmetic reasoning. Electrophysiological studies in humans have demonstrated that processing incorrect arithmetic equations (e.g., 2 + 2 = 5) elicits a prominent event-related potential (ERP) compared to processing correct equations (e.g., 2 + 2 = 4). In the present study, we investigated the neural substrates of this process using event-related functional magnetic resonance imaging (fMRI). Subjects were presented with arithmetic equations and asked to indicate whether the solution displayed was correct or incorrect. We found greater activation to incorrect, compared to correct equations, in the left dorsolateral prefrontal cortex (DLPFC, BA 46) and the left ventrolateral prefrontal cortex (VLPFC, BA 47). Our results provide the first brain imaging evidence for differential processing of incorrect vs. correct equations. The prefrontal cortex activation observed in processing incorrect equations overlaps with brain areas known to be involved in working memory and interference processing. The DLPFC region differentially activated by incorrect equations was also involved in overall arithmetic processing, whereas the VLPFC was activated only during the differential processing of incorrect equations. Differential response to correct and incorrect arithmetic equations was not observed in parietal cortex regions such as the angular gyrus and intra-parietal sulcus, which are known to play a specific role in performing arithmetic computations. The pattern of brain response observed is consistent with the hypothesis that processing incorrect equations involves detection of an incorrect answer and resolution of the interference between the internally computed and externally presented incorrect answer. More specifically, greater activation during processing of incorrect equations appears to reflect additional operations involved in maintaining the results in working memory, while subjects attempt to resolve the conflict and select a response. These findings allow us to further delineate and dissociate the contributions of prefrontal and parietal cortices to arithmetic reasoning.

Abstract

We used fMRI to investigate developmental changes in brain activation during a Stroop color-word interference task. A positive correlation was observed between age and Stroop-related activation (n = 30) in the left lateral prefrontal cortex, the left anterior cingulate, and the left parietal and parieto-occipital cortices. No regions showed a negative correlation between activation and age. We further investigated age-related differences by stratifying the sample into three age groups: children (ages 7-11), adolescents (ages 12-16), and young adults (ages 18-22). Young adult subjects (n = 11) displayed significant activation in the inferior and middle frontal gyri bilaterally, the left anterior cingulate, and bilateral inferior and superior parietal lobules. Between-group comparisons revealed that young adults had significantly greater activation than adolescent subjects (n = 11) in the left middle frontal gyrus and that young adults showed significantly greater activation than children (n = 8) in the anterior cingulate and left parietal and parieto-occipital regions, as well as in the left middle frontal gyrus. Compared to children, both adult and adolescent subjects exhibited significantly greater activation in the parietal cortex. Adult and adolescent groups, however, did not differ in activation for this region. Together, these data suggest that Stroop task-related functional development of the parietal lobe occurs by adolescence. In contrast, prefrontal cortex function contributing to the Stroop interference task continues to develop into adulthood. This neuromaturational process may depend on increased ability to recruit focal neural resources with age. Findings from this study, the first developmental fMRI investigation of the Stroop interference task, provide a template with which normal development and neurodevelopmental disorders of prefrontal cortex function can be assessed.

Abstract

Episodic and semantic memory are two forms of declarative memory which appear to function in distinct yet interdependent ways. Here we provide direct evidence for a functional relationship between these two memory systems by showing that left lateral temporal lobe regions involved in semantic memory play an important role in accurate episodic memory retrieval.

Abstract

Females with fragile X syndrome, the most common form of inherited developmental and learning problems, are known to be impaired in executive function. The current study is the first to investigate the performance of females with fragile X on a cognitive interference task utilizing functional magnetic resonance imaging (fMRI). Fourteen females with fragile X and 14 age-matched healthy controls were imaged while they performed a counting Stroop interference task. Compared to controls, females with fragile X appeared to have longer reaction times during the interference condition of the task, and adopted a strategy trading speed for accuracy. Females with fragile X also had a significantly different pattern of activation than controls. Whereas controls showed significant activation in the inferior/middle frontal gyrus and inferior/superior parietal lobe, females with fragile X showed more extensive activation in the anterior region of the prefrontal cortex, and failed to show expected activation in the inferior/superior parietal lobe. Further, between-group analyses revealed that females with fragile X had reduced activation in the left orbitofrontal gyrus, thought to be involved in modulating goal-directed behavior. Females with fragile X also demonstrated a markedly different pattern of deactivation from controls. These findings suggest that deficits in cognitive interference processing during the counting Stroop task observed in females with fragile X may arise from inability to appropriately recruit and modulate lateral prefrontal and parietal resources.

Abstract

Writing is a uniquely human skill that we utilize nearly everyday. Lesion studies in patients with Gerstmann's syndrome have pointed to the parietal cortex as being critical for writing. Very little information is, however, available about the precise anatomical location of brain regions subserving writing in normal healthy individuals. In this study, we used functional magnetic resonance imaging (fMRI) to investigate parietal lobe function during writing to dictation. Significant clusters of activation were observed in left superior parietal lobe (SPL) and the dorsal aspects of the inferior parietal cortex (IPC) bordering the SPL. Localized clusters of activation were also observed in the left premotor cortex, sensorimotor cortex and supplementary motor area. No activation cluster was observed in the right hemisphere. These results clearly indicate that writing appears to be primarily organized in the language-dominant hemisphere. Further analysis revealed that within the parietal cortex, activation was significantly greater in the left SPL, compared to left IPC. Together with lesion studies, findings from the present study provide further evidence for the essential role of the left SPL in writing. Deficits to the precise left hemisphere parietal cortex regions identified in the present study may specifically underlie disorders of writing observed in Gerstmann's syndrome and apractic agraphia.

Abstract

Turner syndrome (TS), a genetic disorder characterized by the absence of an X chromosome in females, has been associated with cognitive and visuo-spatial processing impairments. We utilized functional MRI (fMRI) to investigate the neural substrates that underlie observed deficits in executive functioning and visuo-spatial processing. Eleven females with TS and 14 typically developing females (ages 7-20) underwent fMRI scanning while performing 1-back and 2-back versions of a standard visuo-spatial working memory (WM) task. On both tasks, TS subjects performed worse than control subjects. Compared with controls, TS subjects showed increased activation in the left and right supramarginal gyrus (SMG) during the 1-back task and decreased activation in these regions during the 2-back task. In addition, decreased activation in the left and right dorsolateral prefrontal cortex (DLPFC) and caudate nucleus was observed during the 2-back task in TS subjects. Activation differences localized to the SMG, in the inferior parietal lobe, may reflect deficits in visuo-spatial encoding and WM storage mechanisms in TS. In addition, deficits in the DLPFC and caudate may be related to deficits in executive function during WM performance. Together these findings point to deficits in frontal-striatal and frontal-parietal circuits subserving multiple WM functions in TS.

Abstract

Chronic alcoholism is associated with impairment in sustained attention and visual working memory. Thus, alcoholics have reduced ability, but not necessarily inability, to perform these executive tasks, assumed to be subserved by regions of prefrontal cortex. To identify neural substrates associated with this impairment, we used functional MRI (fMRI) to determine whether alcoholics invoke the same or different brain systems as controls when engaged in working memory tasks that the two groups were able to perform at equivalent levels. The fMRI spatial working memory paradigm instructed subjects to respond with a button press when a target position was either in the center of the field (match to center) or matched the spatial position of one presented two items previously (match 2-back) or to rest. Using whole-brain fMRI, alcoholics showed diminished activation frontal cortical systems compared to controls (bilateral dorsolateral prefrontal cortex) when responding 2-back vs rest. In the center vs rest contrast, the control group compared with the alcoholic group activated a large expanse of prefrontal cortex (including Brodmann areas 9, 10, and 45), whereas there was significantly greater activation by the alcoholic group relative to the control group localized more posteriorly and inferiorly in the frontal cortex (area 47). Examination of within group activation patterns revealed two different patterns of activation: the control group exhibited activation of the dorsal ("Where?") stream for visual spatial working memory processing, whereas the alcoholic group exhibited activation of the ventral ("What?") stream and declarative memory systems to accomplish the spatial working memory task. The differences in the pattern of brain activations exhibited by the alcoholic and control groups, despite equivalence in behavioral performance, is consistent with a functional reorganization of the brain systems invoked by alcoholic individuals or invocation of an inappropriate brain system when engaged in a visual spatial task requiring working memory.

Abstract

Fragile X syndrome is a neurogenetic disorder that is the most common known heritable cause of neurodevelopmental disability. This study examined the neural substrates of working memory in female subjects with fragile X syndrome. Possible correlations among behavioral measures, brain activation, and the FMR1 gene product (FMRP expression), as well as between IQ and behavioral measures, were investigated.Functional magnetic resonance imaging was used to examine visuospatial working memory in 10 female subjects with fragile X syndrome and 15 typically developing female subjects (ages 10-23 years). Subjects performed standard 1-back and 2-back visuospatial working memory tasks. Brain activation was examined in four regions of the cortex known to play a critical role in visuospatial working memory. Correlations between behavioral, neuroimaging, and molecular measures were examined.Relative to the comparison group, subjects with fragile X syndrome performed significantly worse on the 2-back task but not on the 1-back task. In a region-of-interest analysis focused on the inferior frontal gyrus, middle frontal gyrus, superior parietal lobule, and supramarginal gyrus, comparison subjects showed significantly increased brain activation between the 1-back and 2-back tasks, but subjects with fragile X syndrome showed no change in activation between the two tasks. Significant correlations were found in comparison subjects between activation in the frontal and parietal regions and the rate of correct responses on the 2-back task, but not on the 1-back task. In subjects with fragile X syndrome, significant correlations were found during the 2-back task between FMRP expression and activation in the right inferior and bilateral middle frontal gyri and the bilateral supramarginal gyri.Subjects with fragile X syndrome are unable to modulate activation in the prefrontal and parietal cortex in response to an increasing working memory load, and these deficits are related to a lower level of FMRP expression in fragile X syndrome subjects than in normal comparison subjects. The observed correlations between biological markers and brain activation provide new evidence for links between gene expression and cognition.

Abstract

This study was an examination of basal ganglia dysfunction in schizophrenia using functional magnetic resonance imaging (fMRI).The authors used a motor sequencing task to investigate activation of the caudate, anterior putamen plus globus pallidus, and posterior putamen plus globus pallidus in eight subjects with schizophrenia and 12 group-matched comparison subjects. Differences in activation of the thalamus, the target of direct output from the globus pallidus, were also examined.The schizophrenia subjects showed significant bilateral deficits in the posterior putamen, globus pallidus, and thalamus but not the anterior putamen plus globus pallidus or caudate. Functional connectivity analysis revealed that the deficits in thalamic activation were related to deficits in posterior putamen and globus pallidus activation.These results provide fMRI evidence for basal ganglia dysfunction in subjects with schizophrenia and suggest that this deficit results in disrupted outflow to the thalamus. These deficits may underlie the behavioral impairments in goal-directed action observed in schizophrenia.

Abstract

The MR images of 16 men with dyslexia and 14 control subjects were compared using a voxel-based analysis. Evidence of decreases in gray matter in dyslexic subjects, most notably in the left temporal lobe and bilaterally in the temporoparietooccipital juncture, but also in the frontal lobe, caudate, thalamus, and cerebellum, was found. Widely distributed morphologic differences affecting several brain regions may contribute to the deficits associated with dyslexia.

Abstract

The authors recorded event-related brain potentials (ERPs) to picture primes and word targets (picture-name verification task) in patients with Alzheimer's disease (AD) and in elderly and young participants. N400 was more negative to words that did not match pictures than to words that did match pictures in all groups: In the young, this effect was significant at all scalp sites; in the elderly, it was only at central-parietal sites; and in AD patients, it was limited to right central-parietal sites. Among AD patients pretested with a confrontation-naming task to identify pictures they could not name, neither the N400 priming effect nor its scalp distribution was affected by ability to name pictures correctly. This ERP evidence of spared knowledge of these items was complemented by 80% performance accuracy. Thus, although the name of an item may be inaccessible in confrontation naming, N400 shows that knowledge is intact enough to prime cortical responses.

Abstract

Inhibitory control and performance monitoring are critical executive functions of the human brain. Lesion and imaging studies have shown that the inferior frontal cortex plays an important role in inhibition of inappropriate response. In contrast, specific brain areas involved in error processing and their relation to those implicated in inhibitory control processes are unknown. In this study, we used a random effects model to investigate error-related brain activity associated with failure to inhibit response during a Go/NoGo task. Error-related brain activation was observed in the rostral aspect of the right anterior cingulate (BA 24/32) and adjoining medial prefrontal cortex, the left and right insular cortex and adjoining frontal operculum (BA 47) and left precuneus/posterior cingulate (BA 7/31/29). Brain activation related to response inhibition and competition was observed bilaterally in the dorsolateral prefrontal cortex (BA 9/46), pars triangularis region of the inferior frontal cortex (BA 45/47), premotor cortex (BA 6), inferior parietal lobule (BA 39), lingual gyrus and the caudate, as well as in the right dorsal anterior cingulate cortex (BA 24). These findings provide evidence for a distributed error processing system in the human brain that overlaps partially, but not completely, with brain regions involved in response inhibition and competition. In particular, the rostal anterior cingulate and posterior cingulate/precuneus as well as the left and right anterior insular cortex were activated only during error processing, but not during response competition, inhibition, selection, or execution. Our results also suggest that the brain regions involved in the error processing system overlap with brain areas implicated in the formulation and execution of articulatory plans.

Abstract

Functional brain imaging studies of working memory (WM) in schizophrenia have yielded inconsistent results regarding deficits in the dorsolateral prefrontal (DLPFC) and parietal cortices. In spite of its potential importance in schizophrenia, there have been few investigations of WM deficits using auditory stimuli and no functional imaging studies have attempted to relate brain activation during auditory WM to positive and negative symptoms of schizophrenia. We used a two-back auditory WM paradigm in a functional MRI study of men with schizophrenia (N = 11) and controls (N = 13). Region of interest analysis was used to investigate group differences in activation as well as correlations with symptom scores from the Brief Psychiatric Rating Scale. Patients with schizophrenia performed significantly worse and were slower than control subjects in the WM task. Patients also showed decreased lateralization of activation and significant WM related activation deficits in the left and right DLPFC, frontal operculum, inferior parietal, and superior parietal cortex but not in the anterior cingulate or superior temporal gyrus. These results indicate that in addition to the prefrontal cortex, parietal cortex function is also disrupted during WM in schizophrenia. Withdrawal-retardation symptom scores were inversely correlated with frontal operculum activation. Thinking disturbance symptom scores were inversely correlated with right DLPFC activation. Our findings suggest an association between thinking disturbance symptoms, particularly unusual thought content, and disrupted WM processing in schizophrenia.

Abstract

Children with velocardiofacial syndrome (VCFS) often have deficits in mathematical reasoning. Previous research has suggested that structural abnormalities in the parietal lobe region might underlie these deficits. The present study utilized functional magnetic resonance imaging (fMRI) to explore the relationship between brain function and mathematical performance in VCFS.Eight children with VCFS and eight comparison subjects underwent fMRI scanning and completed an arithmetic computation task.In the VCFS group, increased activation was observed in the left supramarginal gyrus (LSMG) as the task difficulty increased.Aberrant LSMG activation, possibly due to structural deficits of the left parietal lobe, may explain decrements in arithmetic performance observed in VCFS.

Abstract

The basal ganglia (BG) are thought to play a critical role in motor planning and movement sequencing. While electrophysiological and imaging studies have shown that the dorso-lateral prefrontal cortex (DLPFC) is involved in working memory (WM), the involvement of the BG in this process is not well understood. We used a motor sequencing task to investigate the differential role of BG nuclei in memory-guided movement. Significant activation was observed in the DLPFC and posterior putamen and globus pallidus (GP), with a trend in the caudate and no differences in the anterior putamen. We then investigated the effect of BG outflow on thalamic activation using functional connectivity analysis. Activation in the posterior putamen + GP was found to be correlated with thalamic activation only in the hemisphere contralateral to movement. These results provide the first fMRI evidence that the BG may modulate activity in the thalamus during working memory-guided movement sequencing. Our findings suggest that the BG activation may reflect increased motor sequencing demands during the memory-guided movement condition and, specifically, that the posterior putamen and GP may play a role in maintenance of representations in WM in a manner that contributes to planning and temporal organization of motor sequencing.

Abstract

Perceiving a complex visual scene and encoding it into memory involves a hierarchical distributed network of brain regions, most notably the hippocampus (HIPP), parahippocampal gyrus (PHG), lingual gyrus (LNG), and inferior frontal gyrus (IFG). Lesion and imaging studies in humans have suggested that these regions are involved in spatial information processing as well as novelty and memory encoding; however, the relative contributions of these regions of interest (ROIs) are poorly understood. This study investigated regional dissociations in spatial information and novelty processing in the context of memory encoding using a 2 x 2 factorial design with factors Novelty (novel vs. repeated) and Stimulus (viewing scenes with rich vs. poor spatial information). Greater activation was observed in the right than left hemisphere; however, hemispheric effects did not differ across regions, novelty, or stimulus type. Significant novelty effects were observed in all four regions. A significant ROI x Stimulus interaction was observed - spatial information processing effects were largest effects in the LNG, significant in the PHG and HIPP and nonsignificant in the IFG. Novelty processing was stimulus dependent in the LNG and stimulus independent in the PHG, HIPP, and IFG. Analysis of the profile of Novelty x Stimulus interaction across ROIs provided evidence for a hierarchical independence in novelty processing characterized by increased dissociation from spatial information processing. Despite these differences in spatial information processing, memory performance for novel scenes with rich and poor spatial information was not significantly different. Memory performance was inversely correlated with right IFG activation, suggesting the involvement of this region in strategically flawed encoding effort. Stepwise regression analysis revealed that memory encoding accounted for only a small fraction of the variance (< 16%) in medial temporal lobe activation. The implications of these results for spatial information, novelty, and memory processing in each stage of the distributed network are discussed.

Abstract

Lesion and brain-imaging studies have implicated the prefrontal and parietal cortices in arithmetic processing, but do not exclude the possibility that these brain areas are also involved in nonarithmetic operations. In the present study, we used functional magnetic resonance imaging to explore which brain areas contribute uniquely to numeric computation. Task difficulty was manipulated in a factorial design by varying the number of operands and the rate of stimulus presentation. Both manipulations increased the number of operations to be performed in unit time. Manipulating the number of operands allowed us to investigate the specific effect of calculation, while manipulating the rate of presentation allowed us to increase task difficulty independent of calculation. We found quantitative changes in activation patterns in the prefrontal and parietal cortices as well as the recruitment of additional brain regions, including the caudate and midcerebellar cortex, with increasing task difficulty. More importantly, the main effect of arithmetic complexity was observed in the left and right angular gyrus, while the main effect of rate of stimulus presentation was observed in the left insular/orbitofrontal cortex. Our findings indicate a dissociation in prefrontal and parietal cortex function during arithmetic processing and further provide the first evidence for a specific role for the angular gyrus in arithmetic computation independent of other processing demands.

Abstract

Fragile X syndrome, the most common known cause of inherited mental retardation, is caused by alterations of the FMR1 gene encoding the FMRP protein. We investigated the relation between FMRP protein levels and functional brain activation during a working memory task. Our study provides the first evidence for a relation between FMR1 gene expression and neural activity during higher-order cognition. More broadly, our findings provide the first demonstration of how gene-brain-behavior investigations can help to bridge the gap between molecular and systems neuroscience.

Abstract

Lesion and imaging studies to date have not clarified which sub-regions of the parietal lobe are specialized for arithmetic processing, and which perform supporting functions. We used functional magnetic resonance imaging to investigate parietal lobe function during arithmetic processing. Functional optimization was examined by analyzing regional differences in brain activation between perfect (100% accuracy) and imperfect performers. Perfect performers had significantly less activation only in the left angular gyrus, a finding that may be associated with skill mastery and long-term practice effects. The present results provide the first direct evidence of localized functional optimization for arithmetic processing in the human brain.

Abstract

Noises elicit startle blinks that are inhibited when immediately (approximately 100 ms) preceded by non-startling prepulses, perhaps reflecting automatic sensory gating. Startle blinks are facilitated when preceded by prepulses at longer lead intervals, perhaps reflecting strategic processes. Event-related brain potentials (ERPs) and startle blinks were used to investigate the well-documented prepulse inhibition failure in schizophrenia. Blinks and ERPs were recorded from 15 schizophrenic men and 20 age-matched controls to noises alone and to noises preceded by prepulses at 120 (PP120), 500 (PP500) and 4000 ms (PP4000) lead intervals. Neither blinks nor any of the ERP components elicited by the noise alone differentiated schizophrenics from controls, although responses to noises were modified by prepulses differently in the two groups. With the N1 component of the ERP, patients showed normal inhibition but lacked facilitation, and with P2, patients lacked inhibition, but showed normal facilitation. With reflex blinks and P300, inhibition was seen in both groups, but no facilitation. These results suggest that different neural circuits are involved in blink and cortical reflections of startle modification in schizophrenics and controls, with both automatic and strategic processes being impaired in schizophrenia.

Abstract

The basal ganglia are thought to be critically involved in motor control. However, the relative contributions of the various sub-components are not known. Although, in principle, functional magnetic resonance imaging (fMRI) provides adequate resolution to image the basal ganglia at the spatial scale of the individual nuclei, activating these nuclei with fMRI has proven to be difficult. Here we report two tasks, involving externally and self paced sequences of arm movements, which resulted in significant activation of contralateral posterior (post-commissural) putamen and globus pallidus. This activation did not significantly differ between the tasks. In contrast, significant activation of the contralateral and ipsilateral anterior caudate and anterior putamen was observed only during externally paced arm movements. These results suggest a dissociation in the roles of the anterior and posterior dorsal basal ganglia: the anterior caudate and putamen may be involved in sensory to motor mapping and the posterior putamen and globus pallidus may be involved in the motor response itself. The findings support the hypothesis that the basal ganglia may be involved in gating sensory influences onto motor areas.

Abstract

Working memory, the ability to hold and manipulate information 'on-line' in a temporary memory store, is impaired in schizophrenia. This impairment may be characterized within the framework of two opposing theoretical models: (1) central executive as coordinator of component processes of working memory or (2) multiple independent systems of spatial and object memory. In order to test which of these models better explains the working memory deficit of schizophrenia, 14 schizophrenic patients and 12 age- and gender-matched control subjects performed tests of spatial memory (dot location), object memory (shapes, color dots) and a dual paradigm (dot location + shapes). If schizophrenia impairs the central executive, a group-by-task interaction would demonstrate excessively worse performance on the dual than single tasks in schizophrenics relative to controls; however, the absence of an interaction would be consistent with deficits in the multiple working memory systems. The schizophrenic group was significantly impaired on all measures, and both the schizophrenic and control performance was worse on the dual than the single tasks. Despite the schizophrenic group performance deficits on the single tasks, the extent of such deficit did not appear additive and contributive to the dual tasks. The lack of a group-by-task interaction provided no support for the central executive model of dysfunction. Rather, the results uphold the model of working memory deficits arising from compromise of multiple (here spatial and object), relatively independent systems, both of which are affected in schizophrenia.

Abstract

Target detection is the process of bringing a salient stimulus into conscious awareness. Target detection evokes a prominent event-related potential (ERP) component (P3) in the electroencephalogram (EEG). We combined the high spatial resolution of functional magnetic resonance imaging (fMRI) with the high temporal resolution of EEG to investigate the neural generators of the P3. Event-related brain activation (ERBA) and ERPs were computed by time-locked averaging of fMRI and EEG, respectively, recorded using the same paradigm in the same subjects. Target detection elicited significantly greater ERBAs bilaterally in the temporal-parietal cortex, thalamus and anterior cingulate. Spatio-temporal modelling of ERPs based on dipole locations derived from the ERBAs indicated that bilateral sources in the temporal-parietal cortex are the main generators of the P3. The findings provide convergent fMRI and EEG evidence for significant activation of the temporal-parietal cortex 285-610 ms after stimulus onset during target detection. The methods developed here provide a novel multimodal neuroimaging technique to investigate the spatio-temporal aspects of processes underlying brain function.

Abstract

Animal electrocorticogram (ECoG) studies have shown that spatial patterns in the gamma band (>20 Hz) reflect perceptual categorization. Spatio-temporal correlations were investigated in the 20-50 Hz range in search for similar phenomena in human ECoG. ECoGs were recorded in a somatosensory discrimination task from 64-electrode subdural grid arrays, with inter-electrode spacing of 1 cm, overlying somatosensory, motor and superior temporal cortices in 2 patients with intractable epilepsy. Bootstrap techniques were devised to analyze the spatial and temporal characteristics of the correlations. Despite an extensive search, no evidence was found for globally correlated activity related to behavior either in narrow (1.e., 35-45 Hz) or broad (i.e., 20-50 Hz) bands. Spatial patterns, extracted using principal component analysis, could not be classified with respect to stimulus type in any time interval. Instead, spatially and temporally intermittent synchronization was observed between pairs of electrodes in 1 cm X 1 cm regions with high variability within and across trials. The distribution of correlation coefficients differed substantially from background levels at inter-electrode distances of 1 cm and 1.4 cm but not 2 cm or more. The minimum duration of correlation, the decorrelation time, of the ECoG was about 50 msec; the average correlation duration at 1 cm inter-electrode distance was about 150 msec; and the recurrence rate of significant correlation peaks was about 1.3/sec. The findings suggest that the surface diameters of domains of spatially correlated activity underlying perceptual categorization in human gamma band ECoG are limited to less than 2 cm and that the intermittent synchronization observed across separations of 1 cm and 1.4 cm is not solely due to volume conduction. Thus, if such gamma band spatial patterns exist in the human brain, no existing technology would be capable of measuring them at the scalp, and subdural electrode arrays for cortical surface recording would have to have spacings under 5 mm.

Abstract

The effect of frequency mismatch, signal transduction delay and inter-population feedback gain on the interaction of neuronal populations, mediated by long-range excitation, is investigated using physiologically realistic system parameters. Self-consistent solutions for the frequency, amplitude, and relative phase of the component signals are derived for limit cycle oscillations. These solutions predict important qualitative features including discontinuous changes in frequency of oscillation and phase reversal between symmetric and antisymmetric limit cycles. A singularity in the solutions is used to predict parameter regions in which limit cycles do not exist. If limit cycles exist at zero delay, it is shown that limit cycles and quasi-periodic attractors alternate as a function of delay. The implications of these results for estimating physiologically meaningful delays from observed phase shifts in EEG time series are discussed. Spectral peaks for the quasi-periodic attractor occur at m nu 1 +/- n nu 2, where the difference nu 1 - nu 2 is approximately equal to the intrinsic population frequency mismatch delta nu. The cross-correlation function is amplitude modulated with a frequency equal to delta nu/2, indicating that the two populations slip in and out of phase with a mean correlation duration equal to 1/delta nu. These findings underpin the dynamical basis of delay induced "desynchronization" of oscillations reported in computer simulations. Bifurcation diagrams indicate that quasi-periodic attractors exist for a wide range of parameters in the presence of delay in long-range excitation and non-zero frequency mismatch. If the frequency mismatch is sufficiently large and the feedback gain is sufficiently small, quasi-periodic attractors exist for all delays. Delays of a few milliseconds, much smaller than the system time scale, can destabilize limit cycle oscillations. The role of synaptic change in inducing bifurcations of limit cycles to quasi-periodic attractors and vice versa is discussed. The implication of these findings for the generation of chaos in distributed neural systems is discussed.

Abstract

A new implementation of the surface Laplacian derivation (SLD) method is described which reconstructs a realistically shaped, local scalp surface geometry using measured electrode positions, generates a local spectral-interpolated potential distribution function, and estimates the surface Laplacian values through a local planar parametric space using a stable numerical method combining Taylor expansions with the least-squares technique. The implementation is modified for efficient repeated SLD operations on a time series. Examples are shown of applications to evoked potential data. The resolving power of the SLD is examined as a function of the spatial signal-to-noise (SNR) ratio. The analysis suggests that the Laplacian is effective when the spatial SNR is greater than 3. It is shown that spatial low-pass filtering with a Gaussian filter can be used to reduce the effect of noise and recover useful signal if the noise is spatially incoherent.